From 6391622874348d18270512397d7f643ab9aebda4 Mon Sep 17 00:00:00 2001
From: David <forenkram@gmx.de>
Date: Mon, 29 Jun 2020 12:55:59 +0200
Subject: [PATCH] automate generation of pc-S relation ship dicts with
functions module. clean up five patch example
---
LDDsimulation/functions.py | 180 ++++----
.../TP-R-multi-patch-with-inner-patch.py | 74 +--
.../TP-R-multi-patch-with-inner-patch.py | 436 ++++++++++++++++++
.../mesh_studies/run-simulation | 16 +
4 files changed, 554 insertions(+), 152 deletions(-)
create mode 100755 Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/mesh_studies/TP-R-multi-patch-with-inner-patch.py
create mode 100755 Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/mesh_studies/run-simulation
diff --git a/LDDsimulation/functions.py b/LDDsimulation/functions.py
index 8c0b568..430dcb0 100644
--- a/LDDsimulation/functions.py
+++ b/LDDsimulation/functions.py
@@ -8,6 +8,7 @@ import typing as tp
import dolfin as df
import functools as ft
+# RELATIVE PERMEABILITIES #####################################################
# Functions used as relative permeabilty functions for wetting phases
def SpowN(S,N):
return S**N
@@ -76,93 +77,92 @@ def generate_relative_permeability_dicts(
raise(NotImplementedError())
return output
-# class SpcRelation(object):
-# """provide capillary pressure saturation relationships functions."""
-# def __init__(self, Spc_on_subdomains):
-# """build base fuction dictionary"""
-# self._build_base_dict()
-# self._Spc_on_subdomains = Spc_on_subdomains
-# self._build_callables()
-#
-# def _build_base_dict(self):
-# """Build base dictionary."""
-# self.__Spc = {
-# "testSpc": self.testSpc(),
-# }
-#
-# def _build_callables(self):
-# """Build callable dictionaries."""
-# self.symbolic = dict()
-# self.prime_symbolic = dict()
-# self.dolfin = dict()
-#
-# for subdomain, Spc_dict in self._Spc_on_subdomains.items():
-# for Spc_type, parameters in Spc_dict.items():
-# if Spc_type == "testSpc":
-# self.symbolic.update(
-# {subdomain: ft.partialmethod(
-# self.__Spc[Spc_type].S_sym,
-# index=parameters["index"]
-# )},
-# )
-# self.prime_symbolic.update(
-# {subdomain: ft.partial(
-# self.__Spc[Spc_type].S_prime_sym,
-# index=parameters["index"]
-# )},
-# )
-# self.dolfin.update(
-# {subdomain: ft.partial(
-# self.__Spc[Spc_type].S,
-# index=parameters["index"]
-# )},
-# )
-# elif Spc_type == "vanGenuchten":
-# raise(NotImplementedError())
-# else:
-# raise(NotImplementedError())
-#
-# class testSpc(object):
-# """Test S-pc relationship used in R-R paper."""
-#
-# def __init__(self):
-# """Construct testSpc."""
-# print("testSpc")
-#
-# def S(pc, index):
-# """Inverse capillary pressure-saturation-relationship.
-#
-# Inverse capillary pressure-saturation-relationship that will
-# be used by the simulation class
-# this function needs to be monotonically decreasing in the
-# capillary_pressure. Since in the richards case pc=-pw, this
-# becomes as a function of pw a monotonically INCREASING function
-# like in our Richards-Richards paper.
-# However since we unify the treatment in the
-# code for Richards and two-phase, we need the same requierment
-# for both cases, two-phase and Richards.
-# """
-# # inverse capillary pressure-saturation-relationship
-# return df.conditional(pc > 0, 1/((1 + pc)**(1/(index + 1))), 1)
-#
-# def S_sym(pc, index):
-# """Inverse capillary pressure-saturation-relationship.
-#
-# Inverse capillary pressure-saturation-relationship as symbolic
-# expression, that will be used by
-# helpers.generate_exact_solution_expressions()
-# """
-# # inverse capillary pressure-saturation-relationship
-# return 1/((1 + pc)**(1/(index + 1)))
-#
-# # derivative of S-pc relationship with respect to pc.
-# # This is needed for the construction of a analytic solution.
-# def S_prime_sym(pc, index):
-# """Derivative of inverse pc-S-relationship.
-#
-# Derivative of the inverse pc-S-relationship as symbolic
-# expression, that will be used by
-# helpers.generate_exact_solution_expressions()
-# """
-# # inverse capillary pressure-saturation-relationship
-# return -1/((index+1)*(1 + pc)**((index+2)/(index+1)))
+
+# S-Pc RELATIONSHIPS ##########################################################
+def test_S(pc, index):
+ """Inverse capillary pressure-saturation-relationship.
+
+ Inverse capillary pressure-saturation-relationship that will
+ be used by the simulation class
+ this function needs to be monotonically decreasing in the
+ capillary_pressure. Since in the richards case pc=-pw, this
+ becomes as a function of pw a monotonically INCREASING function
+ like in our Richards-Richards paper.
+ However since we unify the treatment in the
+ code for Richards and two-phase, we need the same requierment
+ for both cases, two-phase and Richards.
+ """
+ # inverse capillary pressure-saturation-relationship
+ return df.conditional(pc > 0, 1/((1 + pc)**(1/(index + 1))), 1)
+
+def test_S_sym(pc, index):
+ """Inverse capillary pressure-saturation-relationship.
+
+ Inverse capillary pressure-saturation-relationship as symbolic
+ expression, that will be used by
+ helpers.generate_exact_solution_expressions()
+ """
+ # inverse capillary pressure-saturation-relationship
+ return 1/((1 + pc)**(1/(index + 1)))
+
+# derivative of S-pc relationship with respect to pc.
+# This is needed for the construction of a analytic solution.
+def test_S_prime_sym(pc, index):
+ """Derivative of inverse pc-S-relationship.
+
+ Derivative of the inverse pc-S-relationship as symbolic
+ expression, that will be used by
+ helpers.generate_exact_solution_expressions()
+ """
+ # inverse capillary pressure-saturation-relationship
+ return -1/((index+1)*(1 + pc)**((index+2)/(index+1)))
+
+
+def generate_Spc_dicts(
+ Spc_on_subdomains: tp.Dict[int, tp.Dict[str, tp.Dict[str, float]]]
+ )-> tp.Dict[str, tp.Dict[int, tp.Callable]]:
+ """Generate S-pc dictionaries from definition dict.
+
+ Generate S-pc dictionaries from input definition dictionary
+ Spc_on_subdomains. This dictionary contains for each subdomain a
+ dictionary which in turn contains as key a descriptive string
+ describing which function should be used as S-pc relation for that
+ particular subdomain. The values are parameters for that function type
+ e.g. in the case of Van Genuchten or Brooks and Correy.
+ The supported cases are defined by the if statements
+ below.
+ The output is a dictionary containing three dictionaries, the S-pc
+ relationship for the simulation class as well as a symbolic version and
+ its derivative for exact solution generation.
+ """
+ output = dict()
+ output.update({"symbolic": dict()})
+ output.update({"prime_symbolic": dict()})
+ output.update({"dolfin": dict()})
+ for subdomain, Spc_dict in Spc_on_subdomains.items():
+ for Spc_type, parameters in Spc_dict.items():
+ if Spc_type == "testSpc":
+ output["symbolic"].update(
+ {subdomain: ft.partial(
+ test_S_sym,
+ index=parameters["index"]
+ )},
+ )
+ output["prime_symbolic"].update(
+ {subdomain: ft.partial(
+ test_S_prime_sym,
+ index=parameters["index"]
+ )},
+ )
+ output["dolfin"].update(
+ {subdomain: ft.partial(
+ test_S,
+ index=parameters["index"]
+ )},
+ )
+ elif Spc_type == "vanGenuchten":
+ raise(NotImplementedError())
+ else:
+ raise(NotImplementedError())
+
+ return output
diff --git a/Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/TP-R-multi-patch-with-inner-patch.py b/Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/TP-R-multi-patch-with-inner-patch.py
index eaedb8e..3ac7aa5 100755
--- a/Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/TP-R-multi-patch-with-inner-patch.py
+++ b/Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/TP-R-multi-patch-with-inner-patch.py
@@ -5,13 +5,11 @@ This program sets up an LDD simulation
"""
import dolfin as df
import sympy as sym
-import functools as ft
import functions as fts
import LDDsimulation as ldd
import helpers as hlp
import datetime
import os
-import pandas as pd
import multiprocessing as mp
import domainSubstructuring as dss
@@ -274,7 +272,7 @@ intrinsic_permeability = {
6: 0.01, #10e-3
}
-# rel_perm_generator = func.relative_permeability()
+# relative permeabilties
rel_perm_definition = {
1: {"wetting": "Spow2",
"nonwetting": "oneMinusSpow2"},
@@ -292,66 +290,18 @@ rel_perm_dict = fts.generate_relative_permeability_dicts(rel_perm_definition)
relative_permeability = rel_perm_dict["ka"]
ka_prime = rel_perm_dict["ka_prime"]
-# Spc_on_subdomains = {
-# 1: {"testSpc": {"index": 1}},
-# 2: {"testSpc": {"index": 2}},
-# 3: {"testSpc": {"index": 2}},
-# 4: {"testSpc": {"index": 2}},
-# 5: {"testSpc": {"index": 1}}
-# }
-# Spc = fts.SpcRelation(Spc_on_subdomains)
-# S_pc_sym = Spc.symbolic
-# S_pc_sym_prime = Spc.prime_symbolic
-# sat_pressure_relationship = Spc.dolfin
-
-# this function needs to be monotonically decreasing in the capillary_pressure.
-# since in the richards case pc=-pw, this becomes as a function of pw a mono
-# tonically INCREASING function like in our Richards-Richards paper. However
-# since we unify the treatment in the code for Richards and two-phase, we need
-# the same requierment
-# for both cases, two-phase and Richards.
-def saturation(pc, index):
- # inverse capillary pressure-saturation-relationship
- return df.conditional(pc > 0, 1/((1 + pc)**(1/(index + 1))), 1)
-
-
-def saturation_sym(pc, index):
- # inverse capillary pressure-saturation-relationship
- return 1/((1 + pc)**(1/(index + 1)))
-
-
-# derivative of S-pc relationship with respect to pc. This is needed for the
-# construction of a analytic solution.
-def saturation_sym_prime(pc, index):
- # inverse capillary pressure-saturation-relationship
- return -1/((index+1)*(1 + pc)**((index+2)/(index+1)))
-
-
-# note that the conditional definition of S-pc in the nonsymbolic part will be
-# incorporated in the construction of the exact solution below.
-S_pc_sym = {
- 1: ft.partial(saturation_sym, index=1),
- 2: ft.partial(saturation_sym, index=2),
- 3: ft.partial(saturation_sym, index=2),
- 4: ft.partial(saturation_sym, index=2),
- 5: ft.partial(saturation_sym, index=1)
-}
-
-S_pc_sym_prime = {
- 1: ft.partial(saturation_sym_prime, index=1),
- 2: ft.partial(saturation_sym_prime, index=2),
- 3: ft.partial(saturation_sym_prime, index=2),
- 4: ft.partial(saturation_sym_prime, index=2),
- 5: ft.partial(saturation_sym_prime, index=1)
-}
-
-sat_pressure_relationship = {
- 1: ft.partial(saturation, index=1),
- 2: ft.partial(saturation, index=2),
- 3: ft.partial(saturation, index=2),
- 4: ft.partial(saturation, index=2),
- 5: ft.partial(saturation, index=1)
+# S-pc relation
+Spc_on_subdomains = {
+ 1: {"testSpc": {"index": 1}},
+ 2: {"testSpc": {"index": 2}},
+ 3: {"testSpc": {"index": 2}},
+ 4: {"testSpc": {"index": 2}},
+ 5: {"testSpc": {"index": 1}}
}
+Spc = fts.generate_Spc_dicts(Spc_on_subdomains)
+S_pc_sym = Spc["symbolic"]
+S_pc_sym_prime = Spc["prime_symbolic"]
+sat_pressure_relationship = Spc["dolfin"]
#############################################
# Manufacture source expressions with sympy #
diff --git a/Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/mesh_studies/TP-R-multi-patch-with-inner-patch.py b/Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/mesh_studies/TP-R-multi-patch-with-inner-patch.py
new file mode 100755
index 0000000..3622fa9
--- /dev/null
+++ b/Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/mesh_studies/TP-R-multi-patch-with-inner-patch.py
@@ -0,0 +1,436 @@
+#!/usr/bin/python3
+"""Multi-patch simulation with inner patch.
+
+This program sets up an LDD simulation
+"""
+import dolfin as df
+import sympy as sym
+import functions as fts
+import LDDsimulation as ldd
+import helpers as hlp
+import datetime
+import os
+import multiprocessing as mp
+import domainSubstructuring as dss
+
+# init sympy session
+sym.init_printing()
+
+# PREREQUISITS ###############################################################
+# check if output directory "./output" exists. This will be used in
+# the generation of the output string.
+if not os.path.exists('./output'):
+ os.mkdir('./output')
+ print("Directory ", './output', " created ")
+else:
+ print("Directory ", './output', " already exists. Will use as output \
+ directory")
+
+date = datetime.datetime.now()
+datestr = date.strftime("%Y-%m-%d")
+
+# Name of the usecase that will be printed during simulation.
+use_case = "TP-R-five-domain-with-inner-patch-realistic"
+# The name of this very file. Needed for creating log output.
+thisfile = "TP-R-multi-patch-with-inner-patch.py"
+
+# GENERAL SOLVER CONFIG ######################################################
+# maximal iteration per timestep
+max_iter_num = 1000
+FEM_Lagrange_degree = 1
+
+# GRID AND MESH STUDY SPECIFICATIONS #########################################
+mesh_study = True
+resolutions = {
+ 1: 5e-5,
+ 2: 5e-5,
+ 4: 2e-5,
+ 8: 2e-5,
+ 16: 5e-6,
+ 32: 5e-6,
+ 64: 3e-6,
+ 128: 3e-6,
+ # 256: 1e-6,
+ }
+
+# starttimes gives a list of starttimes to run the simulation from.
+# The list is looped over and a simulation is run with t_0 as initial time
+# for each element t_0 in starttimes.
+starttimes = [0.0]
+timestep_size = 0.001
+number_of_timesteps = 1000
+
+# LDD scheme parameters ######################################################
+Lw1 = 0.5 # /timestep_size
+Lnw1 = Lw1
+
+Lw2 = 0.5 # /timestep_size
+Lnw2 = Lw2
+
+Lw3 = 0.5 # /timestep_size
+Lnw3 = Lw3
+
+Lw4 = 0.5 # /timestep_size
+Lnw4 = Lw4
+
+Lw5 = 0.5 # /timestep_size
+Lnw5 = Lw5
+
+
+lambda13_w= 4
+lambda13_nw= 4
+
+lambda12_w = 4
+lambda12_nw = 4
+
+lambda23_w = 4
+lambda23_nw = 4
+
+lambda24_w = 4
+lambda24_nw= 4
+
+lambda34_w = 4
+lambda34_nw = 4
+
+lambda45_w = 4
+lambda45_nw = 4
+
+lambda15_w = 4
+lambda15_nw = 4
+
+
+include_gravity = True
+debugflag = False
+analyse_condition = False
+
+# I/O CONFIG #################################################################
+# when number_of_timesteps is high, it might take a long time to write all
+# timesteps to disk. Therefore, you can choose to only write data of every
+# plot_timestep_every timestep to disk.
+plot_timestep_every = 4
+# Decide how many timesteps you want analysed. Analysed means, that
+# subsequent errors of the L-iteration within the timestep are written out.
+number_of_timesteps_to_analyse = 8
+
+# fine grained control over data to be written to disk in the mesh study case
+# as well as for a regular simuation for a fixed grid.
+if mesh_study:
+ write_to_file = {
+ # output the relative errornorm (integration in space) w.r.t. an exact
+ # solution for each timestep into a csv file.
+ 'space_errornorms': True,
+ # save the mesh and marker functions to disk
+ 'meshes_and_markers': True,
+ # save xdmf/h5 data for each LDD iteration for timesteps determined by
+ # number_of_timesteps_to_analyse. I/O intensive!
+ 'L_iterations_per_timestep': False,
+ # save solution to xdmf/h5.
+ 'solutions': True,
+ # save absolute differences w.r.t an exact solution to xdmf/h5 file
+ # to monitor where on the domains errors happen
+ 'absolute_differences': True,
+ # analyise condition numbers for timesteps determined by
+ # number_of_timesteps_to_analyse and save them over time to csv.
+ 'condition_numbers': analyse_condition,
+ # output subsequent iteration errors measured in L^2 to csv for
+ # timesteps determined by number_of_timesteps_to_analyse.
+ # Usefull to monitor convergence of the acutal LDD solver.
+ 'subsequent_errors': True
+ }
+else:
+ write_to_file = {
+ 'space_errornorms': True,
+ 'meshes_and_markers': True,
+ 'L_iterations_per_timestep': False,
+ 'solutions': True,
+ 'absolute_differences': True,
+ 'condition_numbers': analyse_condition,
+ 'subsequent_errors': True
+ }
+
+# OUTPUT FILE STRING #########################################################
+output_string = "./output/{}-{}_timesteps{}_P{}".format(
+ datestr, use_case, number_of_timesteps, FEM_Lagrange_degree
+ )
+
+# DOMAIN AND INTERFACE #######################################################
+substructuring = dss.chessBoardInnerPatch()
+interface_def_points = substructuring.interface_def_points
+adjacent_subdomains = substructuring.adjacent_subdomains
+subdomain_def_points = substructuring.subdomain_def_points
+outer_boundary_def_points = substructuring.outer_boundary_def_points
+
+# MODEL CONFIGURATION #########################################################
+isRichards = {
+ 1: True,
+ 2: False,
+ 3: False,
+ 4: False,
+ 5: True,
+ }
+
+# isRichards = {
+# 1: True,
+# 2: True,
+# 3: True,
+# 4: True,
+# 5: True,
+# 6: True
+# }
+
+# Dict of the form: { subdom_num : viscosity }
+viscosity = {
+ 1: {'wetting' :1,
+ 'nonwetting': 1/50},
+ 2: {'wetting' :1,
+ 'nonwetting': 1/50},
+ 3: {'wetting' :1,
+ 'nonwetting': 1/50},
+ 4: {'wetting' :1,
+ 'nonwetting': 1/50},
+ 5: {'wetting' :1,
+ 'nonwetting': 1/50},
+}
+
+# Dict of the form: { subdom_num : density }
+densities = {
+ 1: {'wetting': 997.0, #997
+ 'nonwetting': 1.225}, #1}, #1.225},
+ 2: {'wetting': 997.0, #997
+ 'nonwetting': 1.225}, #1.225},
+ 3: {'wetting': 997.0, #997
+ 'nonwetting': 1.225}, #1.225},
+ 4: {'wetting': 997.0, #997
+ 'nonwetting': 1.225}, #1.225}
+ 5: {'wetting': 997.0, #997
+ 'nonwetting': 1.225}, #1.225},
+}
+gravity_acceleration = 9.81
+# porosities taken from
+# https://www.geotechdata.info/parameter/soil-porosity.html
+# Dict of the form: { subdom_num : porosity }
+porosity = {
+ 1: 0.2, #0.2, # Clayey gravels, clayey sandy gravels
+ 2: 0.2, #0.22, # Silty gravels, silty sandy gravels
+ 3: 0.2, #0.37, # Clayey sands
+ 4: 0.2, #0.2 # Silty or sandy clay
+ 5: 0.2, #
+}
+
+# subdom_num : subdomain L for L-scheme
+L = {
+ 1: {'wetting' :Lw1,
+ 'nonwetting': Lnw1},
+ 2: {'wetting' :Lw2,
+ 'nonwetting': Lnw2},
+ 3: {'wetting' :Lw3,
+ 'nonwetting': Lnw3},
+ 4: {'wetting' :Lw4,
+ 'nonwetting': Lnw4},
+ 5: {'wetting' :Lw5,
+ 'nonwetting': Lnw5},
+}
+
+# interface_num : lambda parameter for the L-scheme on that interface.
+# Note that interfaces are numbered starting from 0, because
+# adjacent_subdomains is a list and not a dict. Historic fuckup, I know
+# We have defined above as interfaces
+# # interface_vertices introduces a global numbering of interfaces.
+# interface_def_points = [interface13_vertices,
+# interface12_vertices,
+# interface23_vertices,
+# interface24_vertices,
+# interface34_vertices,
+# interface45_vertices,
+# interface15_vertices,]
+lambda_param = {
+ 0: {'wetting': lambda13_w,
+ 'nonwetting': lambda13_nw},#
+ 1: {'wetting': lambda12_w,
+ 'nonwetting': lambda12_nw},#
+ 2: {'wetting': lambda23_w,
+ 'nonwetting': lambda23_nw},#
+ 3: {'wetting': lambda24_w,
+ 'nonwetting': lambda24_nw},#
+ 4: {'wetting': lambda34_w,
+ 'nonwetting': lambda34_nw},#
+ 5: {'wetting': lambda45_w,
+ 'nonwetting': lambda45_nw},#
+ 6: {'wetting': lambda15_w,
+ 'nonwetting': lambda15_nw}#
+}
+
+
+# after Lewis, see pdf file
+intrinsic_permeability = {
+ 1: 0.01, # sand
+ 2: 0.01, # sand, there is a range
+ 3: 0.01, #10e-2, # clay has a range
+ 4: 0.01, #10e-3
+ 5: 0.01, #10e-2, # clay has a range
+ 6: 0.01, #10e-3
+}
+
+# relative permeabilties
+rel_perm_definition = {
+ 1: {"wetting": "Spow2",
+ "nonwetting": "oneMinusSpow2"},
+ 2: {"wetting": "Spow3",
+ "nonwetting": "oneMinusSpow3"},
+ 3: {"wetting": "Spow3",
+ "nonwetting": "oneMinusSpow3"},
+ 4: {"wetting": "Spow3",
+ "nonwetting": "oneMinusSpow3"},
+ 5: {"wetting": "Spow2",
+ "nonwetting": "oneMinusSpow2"}
+}
+
+rel_perm_dict = fts.generate_relative_permeability_dicts(rel_perm_definition)
+relative_permeability = rel_perm_dict["ka"]
+ka_prime = rel_perm_dict["ka_prime"]
+
+# S-pc relation
+Spc_on_subdomains = {
+ 1: {"testSpc": {"index": 1}},
+ 2: {"testSpc": {"index": 2}},
+ 3: {"testSpc": {"index": 2}},
+ 4: {"testSpc": {"index": 2}},
+ 5: {"testSpc": {"index": 1}}
+}
+Spc = fts.generate_Spc_dicts(Spc_on_subdomains)
+S_pc_sym = Spc["symbolic"]
+S_pc_sym_prime = Spc["prime_symbolic"]
+sat_pressure_relationship = Spc["dolfin"]
+
+#############################################
+# Manufacture source expressions with sympy #
+#############################################
+x, y = sym.symbols('x[0], x[1]') # needed by UFL
+t = sym.symbols('t', positive=True)
+
+
+p_e_sym = {
+ 1: {'wetting': -7.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
+ 'nonwetting': 0*t },
+ 2: {'wetting': -7.0 - (1.0 + t*t)*(1.0 + x*x),
+ 'nonwetting': (-1.0 -t*(1.0 + x**2) - sym.sqrt(2+t**2)**2)*y**2 },
+ 3: {'wetting': -7.0 - (1.0 + t*t)*(1.0 + x*x),
+ 'nonwetting': (-1.0 -t*(1.0 + x**2) - sym.sqrt(2+t**2)**2)*y**2 },
+ 4: {'wetting': -7.0 - (1.0 + t*t)*(1.0 + x*x),
+ 'nonwetting': (-1.0 -t*(1.0 + x**2) - sym.sqrt(2+t**2)**2)*y**2 },
+ 5: {'wetting': -7.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
+ 'nonwetting': 0*t },
+}
+
+pc_e_sym = hlp.generate_exact_symbolic_pc(
+ isRichards=isRichards,
+ symbolic_pressure=p_e_sym
+ )
+
+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,
+ intrinsic_permeability=intrinsic_permeability,
+ relative_permeability=relative_permeability,
+ relative_permeability_prime=ka_prime,
+ densities=densities,
+ gravity_acceleration=gravity_acceleration,
+ include_gravity=include_gravity,
+ )
+source_expression = exact_solution_example['source']
+exact_solution = exact_solution_example['exact_solution']
+initial_condition = exact_solution_example['initial_condition']
+
+# BOUNDARY CONDITIONS #########################################################
+# Dictionary of dirichlet boundary conditions. If an exact solution case is
+# used, use the hlp.generate_exact_DirichletBC() method to generate the
+# Dirichlet Boundary conditions from the exact solution.
+dirichletBC = hlp.generate_exact_DirichletBC(
+ isRichards=isRichards,
+ outer_boundary_def_points=outer_boundary_def_points,
+ exact_solution=exact_solution
+ )
+# If no exact solution is provided you need to provide a dictionary of boundary
+# conditions. See the definiton of hlp.generate_exact_DirichletBC() to see
+# the structure.
+
+# LOG FILE OUTPUT #############################################################
+# read this file and print it to std out. This way the simulation can produce a
+# log file with ./TP-R-layered_soil.py | tee simulation.log
+f = open(thisfile, 'r')
+print(f.read())
+f.close()
+
+
+# MAIN ########################################################################
+if __name__ == '__main__':
+ # dictionary of simualation parameters to pass to the run function.
+ # mesh_resolution and starttime are excluded, as they get passed explicitly
+ # to achieve parallelisation in these parameters in these parameters for
+ # mesh studies etc.
+ simulation_parameter = {
+ "tol": 1E-14,
+ "debugflag": debugflag,
+ "max_iter_num": max_iter_num,
+ "FEM_Lagrange_degree": FEM_Lagrange_degree,
+ "mesh_study": mesh_study,
+ "use_case": use_case,
+ "output_string": output_string,
+ "subdomain_def_points": subdomain_def_points,
+ "isRichards": isRichards,
+ "interface_def_points": interface_def_points,
+ "outer_boundary_def_points": outer_boundary_def_points,
+ "adjacent_subdomains": adjacent_subdomains,
+ # "mesh_resolution": mesh_resolution,
+ "viscosity": viscosity,
+ "porosity": porosity,
+ "L": L,
+ "lambda_param": lambda_param,
+ "relative_permeability": relative_permeability,
+ "intrinsic_permeability": intrinsic_permeability,
+ "sat_pressure_relationship": sat_pressure_relationship,
+ # "starttime": starttime,
+ "number_of_timesteps": number_of_timesteps,
+ "number_of_timesteps_to_analyse": number_of_timesteps_to_analyse,
+ "plot_timestep_every": plot_timestep_every,
+ "timestep_size": timestep_size,
+ "source_expression": source_expression,
+ "initial_condition": initial_condition,
+ "dirichletBC": dirichletBC,
+ "exact_solution": exact_solution,
+ "densities": densities,
+ "include_gravity": include_gravity,
+ "gravity_acceleration": gravity_acceleration,
+ "write_to_file": write_to_file,
+ "analyse_condition": analyse_condition
+ }
+ for starttime in starttimes:
+ for mesh_resolution, solver_tol in resolutions.items():
+ simulation_parameter.update({"solver_tol": solver_tol})
+ hlp.info(simulation_parameter["use_case"])
+ LDDsim = mp.Process(
+ target=hlp.run_simulation,
+ args=(
+ simulation_parameter,
+ starttime,
+ mesh_resolution
+ )
+ )
+ LDDsim.start()
+ LDDsim.join()
+ # hlp.run_simulation(
+ # mesh_resolution=mesh_resolution,
+ # starttime=starttime,
+ # parameter=simulation_parameter
+ # )
diff --git a/Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/mesh_studies/run-simulation b/Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/mesh_studies/run-simulation
new file mode 100755
index 0000000..0eb4975
--- /dev/null
+++ b/Two-phase-Richards/multi-patch/five_patch_domain_with_inner_patch/mesh_studies/run-simulation
@@ -0,0 +1,16 @@
+#!/bin/bash
+
+[ $# -eq 0 ] && { echo "Usage: $0 simulation_file [logfile_name]"; exit 1; }
+
+SIMULATION_FILE=$1
+SIMULATION=${SIMULATION_FILE%.py}
+LOGFILE_DEFAULT="$SIMULATION.log"
+
+DATE=$(date -I)
+LOGFILE=${2:-$DATE-$LOGFILE_DEFAULT}
+
+GREETING="Simulation $SIMULATION is run on $DATE by $USER"
+
+echo $GREETING
+echo "running $SIMULATION_FILE | tee $LOGFILE"
+./$SIMULATION_FILE | tee $LOGFILE
--
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