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Commit 60d6185f authored by David Seus's avatar David Seus
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fix weird git fuckug

parent 03ca7a10
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......@@ -7,11 +7,36 @@ import typing as tp
import domainPatch as dp
import LDDsimulation as ldd
import functools as ft
import helpers as hlp
#import ufl as ufl
# init sympy session
sym.init_printing()
use_case = "TP-R-two-patch"
solver_tol = 5E-7
############ GRID #######################ü
mesh_resolution = 40
timestep_size = 0.000001
number_of_timesteps = 15
# decide how many timesteps you want analysed. Analysed means, that we write out
# subsequent errors of the L-iteration within the timestep.
number_of_timesteps_to_analyse = 10
starttime = 0
Lw = 5 #/timestep_size
Lnw=Lw
l_param_w = 100
l_param_nw = 100
include_gravity = True
debugflag = True
analyse_condition = False
output_string = "./output/after_reimplementing_gravity_term_number_of_timesteps{}_".format(number_of_timesteps)
##### Domain and Interface ####
# global simulation domain domain
sub_domain0_vertices = [df.Point(-1.0, -1.0),
......@@ -80,53 +105,44 @@ isRichards = {
}
############ GRID #######################ü
mesh_resolution = 50
timestep_size = 0.01
number_of_timesteps = 160
# decide how many timesteps you want analysed. Analysed means, that we write out
# subsequent errors of the L-iteration within the timestep.
number_of_timesteps_to_analyse = 11
starttime = 0
viscosity = {#
# subdom_num : viscosity
1 : {'wetting' :1},
#'nonwetting': 1}, #
2 : {'wetting' :1,
'nonwetting': 1}
'nonwetting': 1/50}
}
porosity = {#
# subdom_num : porosity
1 : 1,#0.22,#
2 : 1#0.022
1 : 0.22,#
2 : 0.0022
}
# Dict of the form: { subdom_num : density }
densities = {
1: {'wetting': 1},
2: {'wetting': 1,
'nonwetting': 1},
1: {'wetting': 997},
2: {'wetting': 997,
'nonwetting': 1.225},
}
gravity_acceleration = 9.81
L = {#
# subdom_num : subdomain L for L-scheme
1 : {'wetting' :0.25},
1 : {'wetting' :Lw},
# 'nonwetting': 0.25},#
2 : {'wetting' :0.25,
'nonwetting': 0.25}
2 : {'wetting' :Lw,
'nonwetting': Lnw}
}
l_param = 40
lambda_param = {#
# subdom_num : lambda parameter for the L-scheme
1 : {'wetting' :l_param},
1 : {'wetting' :l_param_w},
# 'nonwetting': l_param},#
2 : {'wetting' :l_param,
'nonwetting': l_param}
2 : {'wetting' :l_param_w,
'nonwetting': l_param_nw}
}
## relative permeabilty functions on subdomain 1
......@@ -185,7 +201,7 @@ def rel_perm2w_prime(s):
def rel_perm2nw_prime(s):
# relative permeabilty on subdomain1
return 3*(1-s)**2
return -3*(1-s)**2
_rel_perm1w_prime = ft.partial(rel_perm1w_prime)
# _rel_perm1nw_prime = ft.partial(rel_perm1nw_prime)
......@@ -307,87 +323,44 @@ x, y = sym.symbols('x[0], x[1]') # needed by UFL
t = sym.symbols('t', positive=True)
p_e_sym = {
1: {'wetting': 1.0 - (1.0 + t*t)*(1.0 + x*x + y*y)},
2: {'wetting': 1.0 - (1.0 + t*t)*(1.0 + x*x),
'nonwetting': (-t*(1-y - x**2)**2 - sym.sqrt(2+t**2))*y},
1: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x + y*y))}, #*(1-x)**2*(1+x)**2*(1-y)**2},
2: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)), #*(1-x)**2*(1+x)**2*(1+y)**2,
'nonwetting': (-1-t*(1.1+y + x**2))*y**2}, #*(1-x)**2*(1+x)**2*(1+y)**2},
} #-y*y*(sym.sin(-2*t+2*x)*sym.sin(1/2*y-1.2*t)) - t*t*x*(0.5-y)*y*(1-x)
pc_e_sym = {
1: -1*p_e_sym[1]['wetting'],
2: p_e_sym[2]['nonwetting'] - p_e_sym[2]['wetting']
}
# turn above symbolic code into exact solution for dolphin and
# construct the rhs that matches the above exact solution.
dtS = dict()
div_flux = dict()
source_expression = dict()
exact_solution = dict()
initial_condition = dict()
pc_e_sym = dict()
for subdomain, isR in isRichards.items():
dtS.update({subdomain: dict()})
div_flux.update({subdomain: dict()})
source_expression.update({subdomain: dict()})
exact_solution.update({subdomain: dict()})
initial_condition.update({subdomain: dict()})
if isR:
subdomain_has_phases = ["wetting"]
else:
subdomain_has_phases = ["wetting", "nonwetting"]
# conditional for S_pc_prime
pc = pc_e_sym[subdomain]
dtpc = sym.diff(pc, t, 1)
dxpc = sym.diff(pc, x, 1)
dypc = sym.diff(pc, y, 1)
S = sym.Piecewise((S_pc_sym[subdomain](pc), pc > 0), (1, True))
dS = sym.Piecewise((S_pc_sym_prime[subdomain](pc), pc > 0), (0, True))
for phase in subdomain_has_phases:
# Turn above symbolic expression for exact solution into c code
exact_solution[subdomain].update(
{phase: sym.printing.ccode(p_e_sym[subdomain][phase])}
)
# save the c code for initial conditions
initial_condition[subdomain].update(
{phase: sym.printing.ccode(p_e_sym[subdomain][phase].subs(t, 0))}
)
if phase == "nonwetting":
dtS[subdomain].update(
{phase: -porosity[subdomain]*dS*dtpc}
)
else:
dtS[subdomain].update(
{phase: porosity[subdomain]*dS*dtpc}
)
pa = p_e_sym[subdomain][phase]
dxpa = sym.diff(pa, x, 1)
dxdxpa = sym.diff(pa, x, 2)
dypa = sym.diff(pa, y, 1)
dydypa = sym.diff(pa, y, 2)
mu = viscosity[subdomain][phase]
ka = relative_permeability[subdomain][phase]
dka = ka_prime[subdomain][phase]
rho = densities[subdomain][phase]
g = gravity_acceleration
if phase == "nonwetting":
# x part of div(flux) for nonwetting
dxdxflux = -1/mu*dka(1-S)*dS*dxpc*dxpa + 1/mu*dxdxpa*ka(1-S)
# y part of div(flux) for nonwetting
dydyflux = -1/mu*dka(1-S)*dS*dypc*(dypa - rho*g) \
+ 1/mu*dydypa*ka(1-S)
pc_e_sym.update({subdomain: -p_e_sym[subdomain]['wetting'].copy()})
else:
# x part of div(flux) for wetting
dxdxflux = 1/mu*dka(S)*dS*dxpc*dxpa + 1/mu*dxdxpa*ka(S)
# y part of div(flux) for wetting
dydyflux = 1/mu*dka(S)*dS*dypc*(dypa - rho*g) + 1/mu*dydypa*ka(S)
div_flux[subdomain].update({phase: dxdxflux + dydyflux})
contructed_rhs = dtS[subdomain][phase] - div_flux[subdomain][phase]
source_expression[subdomain].update(
{phase: sym.printing.ccode(contructed_rhs)}
pc_e_sym.update({subdomain: p_e_sym[subdomain]['nonwetting'].copy()
- p_e_sym[subdomain]['wetting'].copy()})
symbols = {"x": x,
"y": y,
"t": t}
# turn above symbolic code into exact solution for dolphin and
# construct the rhs that matches the above exact solution.
exact_solution_example = hlp.generate_exact_solution_expressions(
symbols=symbols,
isRichards=isRichards,
symbolic_pressure=p_e_sym,
symbolic_capillary_pressure=pc_e_sym,
saturation_pressure_relationship=S_pc_sym,
saturation_pressure_relationship_prime=S_pc_sym_prime,
viscosity=viscosity,
porosity=porosity,
relative_permeability=relative_permeability,
relative_permeability_prime=ka_prime,
densities=densities,
gravity_acceleration=gravity_acceleration,
include_gravity=include_gravity,
)
# print(f"source_expression[{subdomain}][{phase}] =", source_expression[subdomain][phase])
source_expression = exact_solution_example['source']
exact_solution = exact_solution_example['exact_solution']
initial_condition = exact_solution_example['initial_condition']
# Dictionary of dirichlet boundary conditions.
dirichletBC = dict()
......@@ -431,8 +404,9 @@ write_to_file = {
# initialise LDD simulation class
simulation = ldd.LDDsimulation(tol = 1E-14, LDDsolver_tol = 1E-7, debug = False)
simulation.set_parameters(output_dir = "./output/",#
simulation = ldd.LDDsimulation(tol = 1E-14, LDDsolver_tol=solver_tol, debug=debugflag)
simulation.set_parameters(use_case=use_case,
output_dir = output_string,#
subdomain_def_points = subdomain_def_points,#
isRichards = isRichards,#
interface_def_points = interface_def_points,#
......@@ -454,10 +428,10 @@ simulation.set_parameters(output_dir = "./output/",#
dirichletBC_expression_strings = dirichletBC,#
exact_solution = exact_solution,#
densities=densities,
include_gravity=True,
include_gravity=include_gravity,
write2file = write_to_file,#
)
simulation.initialise()
# simulation.write_exact_solution_to_xdmf()
simulation.run()
simulation.run(analyse_condition=analyse_condition)
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