Module Prepare_pf
@author: Alexandre Sac–Morane alexandre.sac-morane@uclouvain.be
This is the file preparing the phase-field simulations.
Expand source code
import math
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import binary_dilation, binary_erosion
# -----------------------------------------------------------------------------#
def compute_as(dict_user, dict_sample):
'''
Compute solid activity due to vertical pressure applied.
'''
# control of the front
if dict_user['control_front']:
if dict_user['control_technique'] == 'monitor':
compute_as_control(dict_user, dict_sample)
if dict_user['control_technique'] == 'constant':
compute_as_control_cst(dict_user, dict_sample)
# no control of the front
else :
compute_as_no_control(dict_user, dict_sample)
# -----------------------------------------------------------------------------#
def compute_as_control(dict_user, dict_sample):
'''
Compute solid activity due to vertical pressure applied.
'''
# cst
R_gas = dict_user['R_cst']
Temp = dict_user['temperature']
V_m = dict_user['V_m']
# solid activity
a_s = math.exp(dict_user['pressure_applied']*V_m/(R_gas*Temp))
# init
dict_sample['as_map'] = np.zeros((dict_user['n_mesh_y'], dict_user['n_mesh_x']))
# track
as_L = []
# iterate on x
for i_x in range(len(dict_sample['x_L'])):
# check the front profiles
y_front = dict_sample['current_front'][i_x]
# compute control
control = (y_front-dict_user['y_front_L'][-1])*dict_user['control_front_factor']
# track
as_L.append(a_s*(1+control))
# iterate on y
for i_y in range(len(dict_sample['y_L'])):
y = dict_sample['y_L'][i_y]
if y < dict_user['y_max']-dict_user['size_solute_well'] : # in the grain initially
dict_sample['as_map'][-1-i_y, i_x] = a_s*(1+control)
else : # not in the grain initially
dict_sample['as_map'][-1-i_y, i_x] = 1
# track
dict_user['L_L_as'].append(as_L)
# -----------------------------------------------------------------------------#
def compute_as_control_cst(dict_user, dict_sample):
'''
Compute solid activity due to vertical pressure applied.
'''
# cst
R_gas = dict_user['R_cst']
Temp = dict_user['temperature']
V_m = dict_user['V_m']
# solid activity
a_s = math.exp(dict_user['pressure_applied']*V_m/(R_gas*Temp))
a_s_p = a_s*(1+dict_user['control_front_factor'])
a_s_m = a_s*(1-dict_user['control_front_factor'])
# init
dict_sample['as_map'] = np.zeros((dict_user['n_mesh_y'], dict_user['n_mesh_x']))
# track
as_L = []
# iterate on x
for i_x in range(len(dict_sample['x_L'])):
x = dict_sample['x_L'][i_x]
a_s_i_x = a_s_p + (a_s_m-a_s_p)*(x-dict_sample['x_L'][0])/(dict_sample['x_L'][-1]-dict_sample['x_L'][0])
as_L.append(a_s_i_x)
# iterate on y
for i_y in range(len(dict_sample['y_L'])):
y = dict_sample['y_L'][i_y]
if y < dict_user['y_max']-dict_user['size_solute_well'] : # in the grain initially
dict_sample['as_map'][-1-i_y, i_x] = a_s_i_x
else : # not in the grain initially
dict_sample['as_map'][-1-i_y, i_x] = 1
# track
dict_user['L_L_as'].append(as_L)
# -----------------------------------------------------------------------------#
def compute_as_no_control(dict_user, dict_sample):
'''
Compute solid activity due to vertical pressure applied.
'''
# cst
R_gas = dict_user['R_cst']
Temp = dict_user['temperature']
V_m = dict_user['V_m']
# solid activity
a_s = math.exp(dict_user['pressure_applied']*V_m/(R_gas*Temp))
# init
dict_sample['as_map'] = np.zeros((dict_user['n_mesh_y'], dict_user['n_mesh_x']))
# iterate on mesh
for i_x in range(len(dict_sample['x_L'])):
for i_y in range(len(dict_sample['y_L'])):
y = dict_sample['y_L'][i_y]
if y < dict_user['y_max']-dict_user['size_solute_well'] : # in the grain initially
dict_sample['as_map'][-1-i_y, i_x] = a_s
else : # not in the grain initially
dict_sample['as_map'][-1-i_y, i_x] = 1
# -----------------------------------------------------------------------------#
def compute_c(dict_user, dict_sample):
'''
Compute solute concentration map.
'''
# compute bool map
comb_map = compute_bool_map(dict_user, dict_sample)
# initialization
c_map = dict_sample['c_map'].copy()
c_map_new = c_map.copy()
c_removed_map = np.zeros((dict_user['n_mesh_y'], dict_user['n_mesh_x']))
# track solute moved
s_solute_moved = 0
L_p_solute_moved = []
# iterate on x coordinate
for i_x in range(len(dict_sample['x_L'])):
s_solute_moved_i_x = 0 # quantity to move at this x
s_solute_moved_fluid_i_x = 0 # quantity to move to fluid at this x
L_i_y_fluid = [] # list of i_y corresponding to the fluid
# iterate on y coordinate
for i_y in range(len(dict_sample['y_L'])):
# detect if this is the fluid
if dict_sample['current_front'][i_x]-dict_user['size_tube']/2 <= dict_sample['y_L'][i_y] and\
dict_sample['y_L'][i_y] <= dict_sample['current_front'][i_x]+dict_user['size_tube']/2:
L_i_y_fluid.append(i_y)
# detection of solute to move
if not comb_map[-1-i_y, i_x] and c_map_new[-1-i_y, i_x] != dict_user['C_eq']: # threshold value
# compute solute to move
solute_to_move = c_map_new[-1-i_y, i_x] - dict_user['C_eq']
# detect if this solute must go to the fluid
factor = 1.5 # increase the fluid zone
if dict_sample['current_front'][i_x]-factor*dict_user['size_tube']/2 <= dict_sample['y_L'][i_y] and\
dict_sample['y_L'][i_y] <= dict_sample['current_front'][i_x]+factor*dict_user['size_tube']/2:
s_solute_moved_fluid_i_x = s_solute_moved_fluid_i_x + solute_to_move
# reset value to equilibrium
c_map_new[-1-i_y, i_x] = dict_user['C_eq']
# track
s_solute_moved = s_solute_moved + solute_to_move
s_solute_moved_i_x = s_solute_moved_i_x + solute_to_move
c_removed_map[-1-i_y, i_x] = solute_to_move
# iterate on y coordinate of the fluid
for i_y in L_i_y_fluid:
# move solute in the fluid
c_map_new[-1-i_y, i_x] = c_map_new[-1-i_y, i_x] + s_solute_moved_fluid_i_x/len(L_i_y_fluid)
# track
c_removed_map[-1-i_y, i_x] = c_removed_map[-1-i_y, i_x] - s_solute_moved_fluid_i_x/len(L_i_y_fluid)
# search i_y near the front coordinate
L_search = list(abs(np.array(dict_sample['y_L']-dict_sample['current_front'][i_x])))
i_y_f = L_search.index(min(L_search))
as_ij = dict_sample['as_map'][-1-i_y_f, i_x]
# compute tracker
p_solute_moved = s_solute_moved_i_x/(dict_user['C_eq']*as_ij)
L_p_solute_moved.append(p_solute_moved)
# tracker
dict_user['s_solute_moved_L'].append(s_solute_moved)
dict_user['L_L_p_solute_moved'].append(L_p_solute_moved)
dict_user['c_removed_map'] = c_removed_map.copy()
# plot
if 'c_removed_map' in dict_user['L_figures']:
fig, (ax1) = plt.subplots(1,1,figsize=(16,9))
im = ax1.imshow(dict_user['c_removed_map'], interpolation = 'nearest', extent=(dict_sample['x_L'][0],dict_sample['x_L'][-1],dict_sample['y_L'][0],dict_sample['y_L'][-1]))
fig.colorbar(im, ax=ax1)
ax1.set_title(r'Map of c removed',fontsize = 30)
fig.tight_layout()
fig.savefig('plot/map_c_removed.png')
plt.close(fig)
# extract solute from the well
# track mean value
m_c_well = 0
n_c_well = 0
# iterate on the mesh
for i_x in range(len(dict_sample['x_L'])):
for i_y in range(len(dict_sample['y_L'])):
# upper zone
if dict_sample['y_L'][i_y] > dict_user['y_max'] - dict_user['size_solute_well']:
# track the mean value in the upper zone
m_c_well = m_c_well + c_map_new[-1-i_y, i_x]
n_c_well = n_c_well + 1
# change value to have a well zone
c_map_new[-1-i_y, i_x] = dict_user['C_eq']
# track mean
dict_user['m_c_well_L'].append(m_c_well/n_c_well)
# save data
dict_sample['c_map'] = c_map_new.copy()
# -----------------------------------------------------------------------------#
def compute_kc(dict_user, dict_sample):
'''
Compute diffusion map.
'''
# compute bool map
comb_map = compute_bool_map(dict_user, dict_sample)
# plot
if 'diff_map' in dict_user['L_figures']:
fig, (ax1) = plt.subplots(1,1,figsize=(16,9))
im = ax1.imshow(comb_map, interpolation = 'nearest', extent=(dict_sample['x_L'][0],dict_sample['x_L'][-1],dict_sample['y_L'][0],dict_sample['y_L'][-1]))
fig.colorbar(im, ax=ax1)
ax1.set_title(r'Bool',fontsize = 30)
fig.tight_layout()
fig.savefig('plot/map_diffusion.png')
plt.close(fig)
# assign real value
kc_map = comb_map*dict_user['D_solute']
dict_sample['kc_map'] = kc_map
# iterate on the mesh
for i_x in range(len(dict_sample['x_L'])):
for i_y in range(len(dict_sample['y_L'])):
# increase diffusion in the well
if dict_sample['y_L'][i_y] > dict_user['y_max'] - dict_user['size_solute_well']:
dict_sample['kc_map'][-1-i_y, i_x] = dict_sample['kc_map'][-1-i_y,i_x] * 100
# increase diffusion in the tube
elif dict_sample['x_L'][i_x] > dict_user['x_max'] - dict_user['size_tube'] and\
dict_sample['y_L'][i_y] > dict_sample['current_front'][i_x] + dict_user['size_tube']/2:
dict_sample['kc_map'][-1-i_y, i_x] = dict_sample['kc_map'][-1-i_y,i_x] * 100
# -----------------------------------------------------------------------------#
def compute_bool_map(dict_user, dict_sample):
'''
Compute bool map for c and diffusion.
'''
# init
comb_map = np.array(np.zeros((dict_user['n_mesh_y'], dict_user['n_mesh_x'])), dtype = bool)
# add thin fluid film
# iterate on x
for i_x in range(len(dict_sample['x_L'])):
y_front = dict_sample['current_front'][i_x]
# iterate on y
for i_y in range(len(dict_sample['y_L'])):
y = dict_sample['y_L'][i_y]
# thin fluid film
if y_front-dict_user['size_tube']/2 <= y and y <= y_front+dict_user['size_tube']/2:
comb_map[-1-i_y, i_x] = True
else :
comb_map[-1-i_y, i_x] = False
# add tubes
# iterate on the x coordinates
for i_x in range(len(dict_sample['x_L'])):
# tube at the right
if dict_user['x_max'] - dict_user['size_tube'] < dict_sample['x_L'][i_x]:
i_y = 0
while not comb_map[i_y, i_x]:
comb_map[i_y, i_x] = True
i_y = i_y + 1
# add top reservoir
for i_y in range(len(dict_sample['y_L'])):
if dict_sample['y_L'][i_y] > dict_user['y_max'] - dict_user['size_solute_well']:
comb_map[-1-i_y, :] = True
return comb_map
#-------------------------------------------------------------------------------
def write_as_txt(dict_user, dict_sample):
'''
Write a .txt file needed for MOOSE simulation.
This .txt represents the map of the solid activity.
'''
file_to_write = open('data/as.txt','w')
# x
file_to_write.write('AXIS X\n')
line = ''
for x in dict_sample['x_L']:
line = line + str(x)+ ' '
line = line + '\n'
file_to_write.write(line)
# y
file_to_write.write('AXIS Y\n')
line = ''
for y in dict_sample['y_L']:
line = line + str(y)+ ' '
line = line + '\n'
file_to_write.write(line)
# data
file_to_write.write('DATA\n')
for j in range(len(dict_sample['y_L'])):
for i in range(len(dict_sample['x_L'])):
file_to_write.write(str(dict_sample['as_map'][-1-j,i])+'\n')
# close
file_to_write.close()
#-------------------------------------------------------------------------------
def write_kc_txt(dict_user, dict_sample):
'''
Write a .txt file needed for MOOSE simulation.
This .txt represents the map of the diffusion.
'''
file_to_write = open('data/kc.txt','w')
# x
file_to_write.write('AXIS X\n')
line = ''
for x in dict_sample['x_L']:
line = line + str(x)+ ' '
line = line + '\n'
file_to_write.write(line)
# y
file_to_write.write('AXIS Y\n')
line = ''
for y in dict_sample['y_L']:
line = line + str(y)+ ' '
line = line + '\n'
file_to_write.write(line)
# data
file_to_write.write('DATA\n')
for j in range(len(dict_sample['y_L'])):
for i in range(len(dict_sample['x_L'])):
file_to_write.write(str(dict_sample['kc_map'][-1-j,i])+'\n')
# close
file_to_write.close()
#-------------------------------------------------------------------------------
def write_c_txt(dict_user, dict_sample):
'''
Write a .txt file needed for MOOSE simulation.
This .txt represents the map of the solute concentration.
'''
file_to_write = open('data/c.txt','w')
# x
file_to_write.write('AXIS X\n')
line = ''
for x in dict_sample['x_L']:
line = line + str(x)+ ' '
line = line + '\n'
file_to_write.write(line)
# y
file_to_write.write('AXIS Y\n')
line = ''
for y in dict_sample['y_L']:
line = line + str(y)+ ' '
line = line + '\n'
file_to_write.write(line)
# data
file_to_write.write('DATA\n')
for j in range(len(dict_sample['y_L'])):
for i in range(len(dict_sample['x_L'])):
file_to_write.write(str(dict_sample['c_map'][-1-j,i])+'\n')
# close
file_to_write.close()
#-------------------------------------------------------------------------------
def write_eta_txt(dict_user, dict_sample):
'''
Write a .txt file needed for MOOSE simulation.
This .txt represents the map of phase.
'''
file_to_write = open('data/eta.txt','w')
# x
file_to_write.write('AXIS X\n')
line = ''
for x in dict_sample['x_L']:
line = line + str(x)+ ' '
line = line + '\n'
file_to_write.write(line)
# y
file_to_write.write('AXIS Y\n')
line = ''
for y in dict_sample['y_L']:
line = line + str(y)+ ' '
line = line + '\n'
file_to_write.write(line)
# data
file_to_write.write('DATA\n')
for j in range(len(dict_sample['y_L'])):
for i in range(len(dict_sample['x_L'])):
file_to_write.write(str(dict_sample['eta_map'][-1-j,i])+'\n')
# close
file_to_write.close()
#-------------------------------------------------------------------------------
def write_i(dict_user, dict_sample):
'''
Create the .i file to run MOOSE simulation.
The file is generated from a template nammed pf_base.i
'''
file_to_write = open('pf.i','w')
file_to_read = open('pf_base.i','r')
lines = file_to_read.readlines()
file_to_read.close()
j = 0
for line in lines :
j = j + 1
if j == 4:
line = line[:-1] + ' ' + str(len(dict_sample['x_L'])-1)+'\n'
elif j == 5:
line = line[:-1] + ' ' + str(len(dict_sample['y_L'])-1)+'\n'
elif j == 6:
line = line[:-1] + ' ' + str(min(dict_sample['x_L']))+'\n'
elif j == 7:
line = line[:-1] + ' ' + str(max(dict_sample['x_L']))+'\n'
elif j == 8:
line = line[:-1] + ' ' + str(min(dict_sample['y_L']))+'\n'
elif j == 9:
line = line[:-1] + ' ' + str(max(dict_sample['y_L']))+'\n'
elif j == 70:
line = line[:-1] + ' ' + str(1/dict_user['V_m'])+'\n'
elif j == 84:
line = line[:-1] + "'1 "+str(dict_user['kappa_eta'])+" 1'\n"
elif j == 106:
line = line[:-1] + ' ' + str(dict_user['Energy_barrier'])+"'\n"
elif j == 119:
line = line[:-1] + "'" + str(dict_user['C_eq']) + ' ' + str(dict_user['k_diss']) + ' ' + str(dict_user['k_prec']) + "'\n"
elif j == 176 or j == 177 or j == 179 or j == 180:
line = line[:-1] + ' ' + str(dict_user['crit_res']) +'\n'
elif j == 183:
line = line[:-1] + ' ' + str(dict_user['dt_PF']*dict_user['n_t_PF']) +'\n'
elif j == 187:
line = line[:-1] + ' ' + str(dict_user['dt_PF']) +'\n'
file_to_write.write(line)
file_to_write.close()
Functions
def compute_as()-
Select the method to compute solid activity due to vertical pressure applied.
Expand source code
def compute_as(dict_user, dict_sample): ''' Compute solid activity due to vertical pressure applied. ''' # control of the front if dict_user['control_front']: if dict_user['control_technique'] == 'monitor': compute_as_control(dict_user, dict_sample) if dict_user['control_technique'] == 'constant': compute_as_control_cst(dict_user, dict_sample) # no control of the front else : compute_as_no_control(dict_user, dict_sample) def compute_as_control()-
Compute solid activity due to vertical pressure applied with a dynamic control method to ensure flat surface.
Expand source code
def compute_as_control(dict_user, dict_sample): ''' Compute solid activity due to vertical pressure applied. ''' # cst R_gas = dict_user['R_cst'] Temp = dict_user['temperature'] V_m = dict_user['V_m'] # solid activity a_s = math.exp(dict_user['pressure_applied']*V_m/(R_gas*Temp)) # init dict_sample['as_map'] = np.zeros((dict_user['n_mesh_y'], dict_user['n_mesh_x'])) # track as_L = [] # iterate on x for i_x in range(len(dict_sample['x_L'])): # check the front profiles y_front = dict_sample['current_front'][i_x] # compute control control = (y_front-dict_user['y_front_L'][-1])*dict_user['control_front_factor'] # track as_L.append(a_s*(1+control)) # iterate on y for i_y in range(len(dict_sample['y_L'])): y = dict_sample['y_L'][i_y] if y < dict_user['y_max']-dict_user['size_solute_well'] : # in the grain initially dict_sample['as_map'][-1-i_y, i_x] = a_s*(1+control) else : # not in the grain initially dict_sample['as_map'][-1-i_y, i_x] = 1 # track dict_user['L_L_as'].append(as_L) def compute_as_control_cst()-
Compute solid activity due to vertical pressure applied with a given control method to ensure flat interface.
Expand source code
def compute_as_control_cst(dict_user, dict_sample): ''' Compute solid activity due to vertical pressure applied. ''' # cst R_gas = dict_user['R_cst'] Temp = dict_user['temperature'] V_m = dict_user['V_m'] # solid activity a_s = math.exp(dict_user['pressure_applied']*V_m/(R_gas*Temp)) a_s_p = a_s*(1+dict_user['control_front_factor']) a_s_m = a_s*(1-dict_user['control_front_factor']) # init dict_sample['as_map'] = np.zeros((dict_user['n_mesh_y'], dict_user['n_mesh_x'])) # track as_L = [] # iterate on x for i_x in range(len(dict_sample['x_L'])): x = dict_sample['x_L'][i_x] a_s_i_x = a_s_p + (a_s_m-a_s_p)*(x-dict_sample['x_L'][0])/(dict_sample['x_L'][-1]-dict_sample['x_L'][0]) as_L.append(a_s_i_x) # iterate on y for i_y in range(len(dict_sample['y_L'])): y = dict_sample['y_L'][i_y] if y < dict_user['y_max']-dict_user['size_solute_well'] : # in the grain initially dict_sample['as_map'][-1-i_y, i_x] = a_s_i_x else : # not in the grain initially dict_sample['as_map'][-1-i_y, i_x] = 1 # track dict_user['L_L_as'].append(as_L) def compute_as_no_control()-
Compute solid activity due to vertical pressure applied.
Expand source code
def compute_as_no_control(dict_user, dict_sample): ''' Compute solid activity due to vertical pressure applied. ''' # cst R_gas = dict_user['R_cst'] Temp = dict_user['temperature'] V_m = dict_user['V_m'] # solid activity a_s = math.exp(dict_user['pressure_applied']*V_m/(R_gas*Temp)) # init dict_sample['as_map'] = np.zeros((dict_user['n_mesh_y'], dict_user['n_mesh_x'])) # iterate on mesh for i_x in range(len(dict_sample['x_L'])): for i_y in range(len(dict_sample['y_L'])): y = dict_sample['y_L'][i_y] if y < dict_user['y_max']-dict_user['size_solute_well'] : # in the grain initially dict_sample['as_map'][-1-i_y, i_x] = a_s else : # not in the grain initially dict_sample['as_map'][-1-i_y, i_x] = 1 def compute_c()-
Compute solute concentration map.
Expand source code
def compute_c(dict_user, dict_sample): ''' Compute solute concentration map. ''' # compute bool map comb_map = compute_bool_map(dict_user, dict_sample) # initialization c_map = dict_sample['c_map'].copy() c_map_new = c_map.copy() c_removed_map = np.zeros((dict_user['n_mesh_y'], dict_user['n_mesh_x'])) # track solute moved s_solute_moved = 0 L_p_solute_moved = [] # iterate on x coordinate for i_x in range(len(dict_sample['x_L'])): s_solute_moved_i_x = 0 # quantity to move at this x s_solute_moved_fluid_i_x = 0 # quantity to move to fluid at this x L_i_y_fluid = [] # list of i_y corresponding to the fluid # iterate on y coordinate for i_y in range(len(dict_sample['y_L'])): # detect if this is the fluid if dict_sample['current_front'][i_x]-dict_user['size_tube']/2 <= dict_sample['y_L'][i_y] and\ dict_sample['y_L'][i_y] <= dict_sample['current_front'][i_x]+dict_user['size_tube']/2: L_i_y_fluid.append(i_y) # detection of solute to move if not comb_map[-1-i_y, i_x] and c_map_new[-1-i_y, i_x] != dict_user['C_eq']: # threshold value # compute solute to move solute_to_move = c_map_new[-1-i_y, i_x] - dict_user['C_eq'] # detect if this solute must go to the fluid factor = 1.5 # increase the fluid zone if dict_sample['current_front'][i_x]-factor*dict_user['size_tube']/2 <= dict_sample['y_L'][i_y] and\ dict_sample['y_L'][i_y] <= dict_sample['current_front'][i_x]+factor*dict_user['size_tube']/2: s_solute_moved_fluid_i_x = s_solute_moved_fluid_i_x + solute_to_move # reset value to equilibrium c_map_new[-1-i_y, i_x] = dict_user['C_eq'] # track s_solute_moved = s_solute_moved + solute_to_move s_solute_moved_i_x = s_solute_moved_i_x + solute_to_move c_removed_map[-1-i_y, i_x] = solute_to_move # iterate on y coordinate of the fluid for i_y in L_i_y_fluid: # move solute in the fluid c_map_new[-1-i_y, i_x] = c_map_new[-1-i_y, i_x] + s_solute_moved_fluid_i_x/len(L_i_y_fluid) # track c_removed_map[-1-i_y, i_x] = c_removed_map[-1-i_y, i_x] - s_solute_moved_fluid_i_x/len(L_i_y_fluid) # search i_y near the front coordinate L_search = list(abs(np.array(dict_sample['y_L']-dict_sample['current_front'][i_x]))) i_y_f = L_search.index(min(L_search)) as_ij = dict_sample['as_map'][-1-i_y_f, i_x] # compute tracker p_solute_moved = s_solute_moved_i_x/(dict_user['C_eq']*as_ij) L_p_solute_moved.append(p_solute_moved) # tracker dict_user['s_solute_moved_L'].append(s_solute_moved) dict_user['L_L_p_solute_moved'].append(L_p_solute_moved) dict_user['c_removed_map'] = c_removed_map.copy() # plot if 'c_removed_map' in dict_user['L_figures']: fig, (ax1) = plt.subplots(1,1,figsize=(16,9)) im = ax1.imshow(dict_user['c_removed_map'], interpolation = 'nearest', extent=(dict_sample['x_L'][0],dict_sample['x_L'][-1],dict_sample['y_L'][0],dict_sample['y_L'][-1])) fig.colorbar(im, ax=ax1) ax1.set_title(r'Map of c removed',fontsize = 30) fig.tight_layout() fig.savefig('plot/map_c_removed.png') plt.close(fig) # extract solute from the well # track mean value m_c_well = 0 n_c_well = 0 # iterate on the mesh for i_x in range(len(dict_sample['x_L'])): for i_y in range(len(dict_sample['y_L'])): # upper zone if dict_sample['y_L'][i_y] > dict_user['y_max'] - dict_user['size_solute_well']: # track the mean value in the upper zone m_c_well = m_c_well + c_map_new[-1-i_y, i_x] n_c_well = n_c_well + 1 # change value to have a well zone c_map_new[-1-i_y, i_x] = dict_user['C_eq'] # track mean dict_user['m_c_well_L'].append(m_c_well/n_c_well) # save data dict_sample['c_map'] = c_map_new.copy() def compute_kc()-
Compute diffusion map.
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def compute_kc(dict_user, dict_sample): ''' Compute diffusion map. ''' # compute bool map comb_map = compute_bool_map(dict_user, dict_sample) # plot if 'diff_map' in dict_user['L_figures']: fig, (ax1) = plt.subplots(1,1,figsize=(16,9)) im = ax1.imshow(comb_map, interpolation = 'nearest', extent=(dict_sample['x_L'][0],dict_sample['x_L'][-1],dict_sample['y_L'][0],dict_sample['y_L'][-1])) fig.colorbar(im, ax=ax1) ax1.set_title(r'Bool',fontsize = 30) fig.tight_layout() fig.savefig('plot/map_diffusion.png') plt.close(fig) # assign real value kc_map = comb_map*dict_user['D_solute'] dict_sample['kc_map'] = kc_map # iterate on the mesh for i_x in range(len(dict_sample['x_L'])): for i_y in range(len(dict_sample['y_L'])): # increase diffusion in the well if dict_sample['y_L'][i_y] > dict_user['y_max'] - dict_user['size_solute_well']: dict_sample['kc_map'][-1-i_y, i_x] = dict_sample['kc_map'][-1-i_y,i_x] * 100 # increase diffusion in the tube elif dict_sample['x_L'][i_x] > dict_user['x_max'] - dict_user['size_tube'] and\ dict_sample['y_L'][i_y] > dict_sample['current_front'][i_x] + dict_user['size_tube']/2: dict_sample['kc_map'][-1-i_y, i_x] = dict_sample['kc_map'][-1-i_y,i_x] * 100 def compute_bool_map()-
Compute bool map for c and diffusion.
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def compute_bool_map(dict_user, dict_sample): ''' Compute bool map for c and diffusion. ''' # init comb_map = np.array(np.zeros((dict_user['n_mesh_y'], dict_user['n_mesh_x'])), dtype = bool) # add thin fluid film # iterate on x for i_x in range(len(dict_sample['x_L'])): y_front = dict_sample['current_front'][i_x] # iterate on y for i_y in range(len(dict_sample['y_L'])): y = dict_sample['y_L'][i_y] # thin fluid film if y_front-dict_user['size_tube']/2 <= y and y <= y_front+dict_user['size_tube']/2: comb_map[-1-i_y, i_x] = True else : comb_map[-1-i_y, i_x] = False # add tubes # iterate on the x coordinates for i_x in range(len(dict_sample['x_L'])): # tube at the right if dict_user['x_max'] - dict_user['size_tube'] < dict_sample['x_L'][i_x]: i_y = 0 while not comb_map[i_y, i_x]: comb_map[i_y, i_x] = True i_y = i_y + 1 # add top reservoir for i_y in range(len(dict_sample['y_L'])): if dict_sample['y_L'][i_y] > dict_user['y_max'] - dict_user['size_solute_well']: comb_map[-1-i_y, :] = True return comb_map def write_as_txt()-
Write a .txt file for the solid activity needed for MOOSE simulation.
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def write_as_txt(dict_user, dict_sample): ''' Write a .txt file needed for MOOSE simulation. This .txt represents the map of the solid activity. ''' file_to_write = open('data/as.txt','w') # x file_to_write.write('AXIS X\n') line = '' for x in dict_sample['x_L']: line = line + str(x)+ ' ' line = line + '\n' file_to_write.write(line) # y file_to_write.write('AXIS Y\n') line = '' for y in dict_sample['y_L']: line = line + str(y)+ ' ' line = line + '\n' file_to_write.write(line) # data file_to_write.write('DATA\n') for j in range(len(dict_sample['y_L'])): for i in range(len(dict_sample['x_L'])): file_to_write.write(str(dict_sample['as_map'][-1-j,i])+'\n') # close file_to_write.close() def write_kc_txt()-
Write a .txt file for the diffusion coefficient needed for MOOSE simulation.
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def write_kc_txt(dict_user, dict_sample): ''' Write a .txt file needed for MOOSE simulation. This .txt represents the map of the diffusion. ''' file_to_write = open('data/kc.txt','w') # x file_to_write.write('AXIS X\n') line = '' for x in dict_sample['x_L']: line = line + str(x)+ ' ' line = line + '\n' file_to_write.write(line) # y file_to_write.write('AXIS Y\n') line = '' for y in dict_sample['y_L']: line = line + str(y)+ ' ' line = line + '\n' file_to_write.write(line) # data file_to_write.write('DATA\n') for j in range(len(dict_sample['y_L'])): for i in range(len(dict_sample['x_L'])): file_to_write.write(str(dict_sample['kc_map'][-1-j,i])+'\n') # close file_to_write.close() def write_c_txt()-
Write a .txt file for the solute concentration needed for MOOSE simulation.
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def write_c_txt(dict_user, dict_sample): ''' Write a .txt file needed for MOOSE simulation. This .txt represents the map of the solute concentration. ''' file_to_write = open('data/c.txt','w') # x file_to_write.write('AXIS X\n') line = '' for x in dict_sample['x_L']: line = line + str(x)+ ' ' line = line + '\n' file_to_write.write(line) # y file_to_write.write('AXIS Y\n') line = '' for y in dict_sample['y_L']: line = line + str(y)+ ' ' line = line + '\n' file_to_write.write(line) # data file_to_write.write('DATA\n') for j in range(len(dict_sample['y_L'])): for i in range(len(dict_sample['x_L'])): file_to_write.write(str(dict_sample['c_map'][-1-j,i])+'\n') # close file_to_write.close() def write_eta_txt()-
Write a .txt file for the phase variable needed for MOOSE simulation.
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def write_eta_txt(dict_user, dict_sample): ''' Write a .txt file needed for MOOSE simulation. This .txt represents the map of phase. ''' file_to_write = open('data/eta.txt','w') # x file_to_write.write('AXIS X\n') line = '' for x in dict_sample['x_L']: line = line + str(x)+ ' ' line = line + '\n' file_to_write.write(line) # y file_to_write.write('AXIS Y\n') line = '' for y in dict_sample['y_L']: line = line + str(y)+ ' ' line = line + '\n' file_to_write.write(line) # data file_to_write.write('DATA\n') for j in range(len(dict_sample['y_L'])): for i in range(len(dict_sample['x_L'])): file_to_write.write(str(dict_sample['eta_map'][-1-j,i])+'\n') # close file_to_write.close() def write_i()-
Write a .i file (input file from the template file pf_base.i) needed for MOOSE simulation.
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def write_i(dict_user, dict_sample): ''' Create the .i file to run MOOSE simulation. The file is generated from a template nammed pf_base.i ''' file_to_write = open('pf.i','w') file_to_read = open('pf_base.i','r') lines = file_to_read.readlines() file_to_read.close() j = 0 for line in lines : j = j + 1 if j == 4: line = line[:-1] + ' ' + str(len(dict_sample['x_L'])-1)+'\n' elif j == 5: line = line[:-1] + ' ' + str(len(dict_sample['y_L'])-1)+'\n' elif j == 6: line = line[:-1] + ' ' + str(min(dict_sample['x_L']))+'\n' elif j == 7: line = line[:-1] + ' ' + str(max(dict_sample['x_L']))+'\n' elif j == 8: line = line[:-1] + ' ' + str(min(dict_sample['y_L']))+'\n' elif j == 9: line = line[:-1] + ' ' + str(max(dict_sample['y_L']))+'\n' elif j == 70: line = line[:-1] + ' ' + str(1/dict_user['V_m'])+'\n' elif j == 84: line = line[:-1] + "'1 "+str(dict_user['kappa_eta'])+" 1'\n" elif j == 106: line = line[:-1] + ' ' + str(dict_user['Energy_barrier'])+"'\n" elif j == 119: line = line[:-1] + "'" + str(dict_user['C_eq']) + ' ' + str(dict_user['k_diss']) + ' ' + str(dict_user['k_prec']) + "'\n" elif j == 176 or j == 177 or j == 179 or j == 180: line = line[:-1] + ' ' + str(dict_user['crit_res']) +'\n' elif j == 183: line = line[:-1] + ' ' + str(dict_user['dt_PF']*dict_user['n_t_PF']) +'\n' elif j == 187: line = line[:-1] + ' ' + str(dict_user['dt_PF']) +'\n' file_to_write.write(line) file_to_write.close()