From dde2e70da0d92e96a7e3cbd789dcda29e419ecad Mon Sep 17 00:00:00 2001
From: David Seus <david.seus@ians.uni-stuttgart.de>
Date: Fri, 16 Aug 2019 16:51:56 +0200
Subject: [PATCH] add layered soil-case-with-inner-patch

---
 Rechnungen_auszuwerten.txt                    |   4 +
 ...layered_soil_with_inner_patch-realistic.py | 736 ++++++++++++++++++
 .../TP-TP-layered_soil_with_inner_patch.py    |  62 +-
 3 files changed, 771 insertions(+), 31 deletions(-)
 create mode 100644 Rechnungen_auszuwerten.txt
 create mode 100755 TP-TP-layered-soil-case-with-inner-patch/TP-TP-layered_soil_with_inner_patch-realistic.py

diff --git a/Rechnungen_auszuwerten.txt b/Rechnungen_auszuwerten.txt
new file mode 100644
index 0000000..77c4399
--- /dev/null
+++ b/Rechnungen_auszuwerten.txt
@@ -0,0 +1,4 @@
+Rechungen, die noch nicht ausgewertet wurden 
+
+- TP-one-patch (purely positive pc)
+- TP-TP-layered-soil-case-with-inner-patch
diff --git a/TP-TP-layered-soil-case-with-inner-patch/TP-TP-layered_soil_with_inner_patch-realistic.py b/TP-TP-layered-soil-case-with-inner-patch/TP-TP-layered_soil_with_inner_patch-realistic.py
new file mode 100755
index 0000000..850d249
--- /dev/null
+++ b/TP-TP-layered-soil-case-with-inner-patch/TP-TP-layered_soil_with_inner_patch-realistic.py
@@ -0,0 +1,736 @@
+#!/usr/bin/python3
+"""This program sets up a domain together with a decomposition into subdomains
+modelling layered soil. This is used for our LDD article with tp-tp and tp-r
+coupling.
+
+Along with the subdomains and the mesh domain markers are set upself.
+The resulting mesh is saved into files for later use.
+"""
+
+#!/usr/bin/python3
+import dolfin as df
+import mshr
+import numpy as np
+import sympy as sym
+import typing as tp
+import functools as ft
+import domainPatch as dp
+import LDDsimulation as ldd
+import helpers as hlp
+
+# init sympy session
+sym.init_printing()
+
+use_case = "TP-TP-layered-soil-with-inner-patch"
+solver_tol = 1E-6
+
+############ GRID #######################ü
+mesh_resolution = 50
+timestep_size = 0.001
+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 = 0.25  #/timestep_size
+Lnw=Lw
+
+lambda_w = 41
+lambda_nw = 41
+
+include_gravity = False
+debugflag = False
+analyse_condition = False
+
+output_string = "./output/test-nondirichlet_number_of_timesteps{}_".format(number_of_timesteps)
+
+# global domain
+subdomain0_vertices = [df.Point(-1.0,-1.0), #
+                        df.Point(1.0,-1.0),#
+                        df.Point(1.0,1.0),#
+                        df.Point(-1.0,1.0)]
+
+interface12_vertices = [df.Point(-1.0, 0.8),
+                        df.Point(0.3, 0.8),
+                        df.Point(0.5, 0.9),
+                        df.Point(0.8, 0.7),
+                        df.Point(1.0, 0.65)]
+
+
+                        # interface23
+interface23_vertices = [df.Point(-1.0, 0.0),
+                        df.Point(-0.35, 0.0),
+                        # df.Point(6.5, 4.5),
+                        df.Point(0.0, 0.0)]
+
+interface24_vertices = [interface23_vertices[2],
+                        df.Point(0.6, 0.0),
+                        ]
+
+interface25_vertices = [interface24_vertices[1],
+                        df.Point(1.0, 0.0)
+                        ]
+
+
+interface32_vertices = [interface23_vertices[2],
+                        interface23_vertices[1],
+                        interface23_vertices[0]]
+
+
+interface36_vertices = [df.Point(-1.0, -0.6),
+                        df.Point(-0.6, -0.45)]
+
+
+interface46_vertices = [interface36_vertices[1],
+                        df.Point(0.3, -0.25)]
+
+interface56_vertices = [interface46_vertices[1],
+                        df.Point(0.65, -0.6),
+                        df.Point(1.0, -0.7)]
+
+
+
+
+interface34_vertices = [interface36_vertices[1],
+                        interface23_vertices[2]]
+# interface36
+
+interface45_vertices = [interface56_vertices[0],
+                        df.Point(0.7, -0.2),
+                        interface25_vertices[0]
+                        ]
+
+# # subdomain1.
+# subdomain1_vertices = [interface12_vertices[0],
+#                         interface12_vertices[1],
+#                         interface12_vertices[2],
+#                         interface12_vertices[3],
+#                         interface12_vertices[4], # southern boundary, 12 interface
+#                         subdomain0_vertices[2], # eastern boundary, outer boundary
+#                         subdomain0_vertices[3]] # northern boundary, outer on_boundary
+#
+# # vertex coordinates of the outer boundaries. If it can not be specified as a
+# # polygon, use an entry per boundary polygon. This information is used for defining
+# # the Dirichlet boundary conditions. If a domain is completely internal, the
+# # dictionary entry should be 0: None
+# subdomain1_outer_boundary_verts = {
+#     0: [interface12_vertices[4], #
+#         subdomain0_vertices[2], # eastern boundary, outer boundary
+#         subdomain0_vertices[3],
+#         interface12_vertices[0]]
+# }
+#
+
+
+# #subdomain1
+# subdomain2_vertices = [interface23_vertices[0],
+#                         interface23_vertices[1],
+#                         interface23_vertices[2],
+#                         interface23_vertices[3],
+#                         interface23_vertices[4],
+#                         interface23_vertices[5], # southern boundary, 23 interface
+#                         subdomain1_vertices[4], # eastern boundary, outer boundary
+#                         subdomain1_vertices[3],
+#                         subdomain1_vertices[2],
+#                         subdomain1_vertices[1],
+#                         subdomain1_vertices[0] ] # northern boundary, 12 interface
+#
+# subdomain2_outer_boundary_verts = {
+#     0: [interface23_vertices[5],
+#         subdomain1_vertices[4]],
+#     1: [subdomain1_vertices[0],
+#         interface23_vertices[0]]
+# }
+#
+
+# interface_vertices introduces a global numbering of interfaces.
+interface_def_points = [interface12_vertices,
+                        interface23_vertices,
+                        interface24_vertices,
+                        interface25_vertices,
+                        interface34_vertices,
+                        interface36_vertices,
+                        interface45_vertices,
+                        interface46_vertices,
+                        interface56_vertices,
+                        ]
+adjacent_subdomains = [[1,2],
+                       [2,3],
+                       [2,4],
+                       [2,5],
+                       [3,4],
+                       [3,6],
+                       [4,5],
+                       [4,6],
+                       [5,6]
+                       ]
+
+# subdomain1.
+subdomain1_vertices = [interface12_vertices[0],
+                        interface12_vertices[1],
+                        interface12_vertices[2],
+                        interface12_vertices[3],
+                        interface12_vertices[4], # southern boundary, 12 interface
+                        subdomain0_vertices[2], # eastern boundary, outer boundary
+                        subdomain0_vertices[3]] # northern boundary, outer on_boundary
+
+# vertex coordinates of the outer boundaries. If it can not be specified as a
+# polygon, use an entry per boundary polygon. This information is used for defining
+# the Dirichlet boundary conditions. If a domain is completely internal, the
+# dictionary entry should be 0: None
+subdomain1_outer_boundary_verts = {
+    0: [subdomain1_vertices[4], #
+        subdomain1_vertices[5], # eastern boundary, outer boundary
+        subdomain1_vertices[6],
+        subdomain1_vertices[0]]
+}
+
+#subdomain1
+subdomain2_vertices = [interface23_vertices[0],
+                        interface23_vertices[1],
+                        interface23_vertices[2],
+                        interface24_vertices[1],
+                        interface25_vertices[1], # southern boundary, 23 interface
+                        subdomain1_vertices[4], # eastern boundary, outer boundary
+                        subdomain1_vertices[3],
+                        subdomain1_vertices[2],
+                        subdomain1_vertices[1],
+                        subdomain1_vertices[0] ] # northern boundary, 12 interface
+
+subdomain2_outer_boundary_verts = {
+    0: [subdomain2_vertices[9],
+        subdomain2_vertices[0]],
+    1: [subdomain2_vertices[4],
+        subdomain2_vertices[5]]
+}
+
+
+subdomain3_vertices = [interface36_vertices[0],
+                       interface36_vertices[1],
+                       # interface34_vertices[0],
+                       interface34_vertices[1],
+                       # interface32_vertices[0],
+                       interface32_vertices[1],
+                       interface32_vertices[2]
+                       ]
+
+subdomain3_outer_boundary_verts = {
+    0: [subdomain3_vertices[4],
+        subdomain3_vertices[0]]
+}
+
+
+# subdomain3
+subdomain4_vertices = [interface46_vertices[0],
+                       interface46_vertices[1],
+                       interface45_vertices[1],
+                       interface24_vertices[1],
+                       interface24_vertices[0],
+                       interface34_vertices[1]
+                       ]
+
+subdomain4_outer_boundary_verts = None
+
+subdomain5_vertices = [interface56_vertices[0],
+                       interface56_vertices[1],
+                       interface56_vertices[2],
+                       interface25_vertices[1],
+                       interface25_vertices[0],
+                       interface45_vertices[1],
+                       interface45_vertices[0]
+]
+
+subdomain5_outer_boundary_verts = {
+    0: [subdomain5_vertices[2],
+        subdomain5_vertices[3]]
+}
+
+
+
+subdomain6_vertices = [subdomain0_vertices[0],
+                       subdomain0_vertices[1], # southern boundary, outer boundary
+                       interface56_vertices[2],
+                       interface56_vertices[1],
+                       interface56_vertices[0],
+                       interface36_vertices[1],
+                       interface36_vertices[0]
+                       ]
+
+subdomain6_outer_boundary_verts = {
+    0: [subdomain6_vertices[6],
+        subdomain6_vertices[0],
+        subdomain6_vertices[1],
+        subdomain6_vertices[2]]
+}
+
+
+subdomain_def_points = [subdomain0_vertices,#
+                      subdomain1_vertices,#
+                      subdomain2_vertices,#
+                      subdomain3_vertices,#
+                      subdomain4_vertices,
+                      subdomain5_vertices,
+                      subdomain6_vertices
+                      ]
+
+
+# if a subdomain has no outer boundary write None instead, i.e.
+# i: None
+# if i is the index of the inner subdomain.
+outer_boundary_def_points = {
+    # subdomain number
+    1: subdomain1_outer_boundary_verts,
+    2: subdomain2_outer_boundary_verts,
+    3: subdomain3_outer_boundary_verts,
+    4: subdomain4_outer_boundary_verts,
+    5: subdomain5_outer_boundary_verts,
+    6: subdomain6_outer_boundary_verts
+}
+
+
+isRichards = {
+    1: False,
+    2: False,
+    3: False,
+    4: False,
+    5: False,
+    6: False
+    }
+
+# 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},
+    6: {'wetting' :1,
+         'nonwetting': 1/50},
+}
+
+# Dict of the form: { subdom_num : density }
+densities = {
+    1: {'wetting': 997,  #997
+         'nonwetting': 1.225},  #1},  #1.225},
+    2: {'wetting': 997,  #997
+         'nonwetting': 1.225},  #1.225},
+    3: {'wetting': 997,  #997
+         'nonwetting': 1.225},  #1.225},
+    4: {'wetting': 997,  #997
+         'nonwetting': 1.225},  #1.225}
+    5: {'wetting': 997,  #997
+         'nonwetting': 1.225},  #1.225},
+    6: {'wetting': 997,  #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: 0.22,  #0.22, # Silty gravels, silty sandy gravels
+    3: 0.22,  #0.37, # Clayey sands
+    4: 0.27,  #0.2 # Silty or sandy clay
+    5: 0.2,  #
+    6: 0.02,  #
+}
+
+# subdom_num : subdomain L for L-scheme
+L = {
+    1: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    2: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    3: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    4: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    5: {'wetting' :Lw,
+         'nonwetting': Lnw},
+    6: {'wetting' :Lw,
+         'nonwetting': Lnw}
+}
+
+# subdom_num : lambda parameter for the L-scheme
+lambda_param = {
+    1: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+    2: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+    3: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+    4: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+    5: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+    6: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+}
+
+
+## relative permeabilty functions on subdomain 1
+def rel_perm1w(s):
+    # relative permeabilty wetting on subdomain1
+    return s**2
+
+
+def rel_perm1nw(s):
+    # relative permeabilty nonwetting on subdomain1
+    return (1-s)**2
+
+
+## relative permeabilty functions on subdomain 2
+def rel_perm2w(s):
+    # relative permeabilty wetting on subdomain2
+    return s**3
+
+
+def rel_perm2nw(s):
+    # relative permeabilty nonwetting on subdosym.cos(0.8*t - (0.8*x + 1/7*y))main2
+    return (1-s)**3
+
+
+_rel_perm1w = ft.partial(rel_perm1w)
+_rel_perm1nw = ft.partial(rel_perm1nw)
+_rel_perm2w = ft.partial(rel_perm2w)
+_rel_perm2nw = ft.partial(rel_perm2nw)
+
+subdomain1_rel_perm = {
+    'wetting': _rel_perm1w,#
+    'nonwetting': _rel_perm1nw
+}
+
+subdomain2_rel_perm = {
+    'wetting': _rel_perm2w,#
+    'nonwetting': _rel_perm2nw
+}
+
+# _rel_perm3 = ft.partial(rel_perm2)
+# subdomain3_rel_perm = subdomain2_rel_perm.copy()
+#
+# _rel_perm4 = ft.partial(rel_perm1)
+# subdomain4_rel_perm = subdomain1_rel_perm.copy()
+
+# dictionary of relative permeabilties on all domains.
+relative_permeability = {
+    1: subdomain1_rel_perm,
+    2: subdomain1_rel_perm,
+    3: subdomain2_rel_perm,
+    4: subdomain2_rel_perm,
+    5: subdomain2_rel_perm,
+    6: subdomain2_rel_perm,
+}
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 1
+def rel_perm1w_prime(s):
+    # relative permeabilty on subdomain1
+    return 2*s
+
+def rel_perm1nw_prime(s):
+    # relative permeabilty on subdomain1
+    return -2*(1-s)
+
+# definition of the derivatives of the relative permeabilities
+# relative permeabilty functions on subdomain 1
+def rel_perm2w_prime(s):
+    # relative permeabilty on subdomain1
+    return 3*s**2
+
+def rel_perm2nw_prime(s):
+    # relative permeabilty on subdomain1
+    return -3*(1-s)**2
+
+_rel_perm1w_prime = ft.partial(rel_perm1w_prime)
+_rel_perm1nw_prime = ft.partial(rel_perm1nw_prime)
+_rel_perm2w_prime = ft.partial(rel_perm2w_prime)
+_rel_perm2nw_prime = ft.partial(rel_perm2nw_prime)
+
+subdomain1_rel_perm_prime = {
+    'wetting': _rel_perm1w_prime,
+    'nonwetting': _rel_perm1nw_prime
+}
+
+
+subdomain2_rel_perm_prime = {
+    'wetting': _rel_perm2w_prime,
+    'nonwetting': _rel_perm2nw_prime
+}
+
+# dictionary of relative permeabilties on all domains.
+ka_prime = {
+    1: subdomain1_rel_perm_prime,
+    2: subdomain1_rel_perm_prime,
+    3: subdomain2_rel_perm_prime,
+    4: subdomain2_rel_perm_prime,
+    5: subdomain2_rel_perm_prime,
+    6: subdomain2_rel_perm_prime,
+}
+
+
+
+# S-pc-relation ship. We use the van Genuchten approach, i.e. pc = 1/alpha*(S^{-1/m} -1)^1/n, where
+# we set alpha = 0, assume m = 1-1/n (see Helmig) and assume that residual saturation is Sw
+# this function needs to be monotonically decreasing in the capillary pressure pc.
+# 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, n_index, alpha):
+#     # inverse capillary pressure-saturation-relationship
+#     return df.conditional(pc > 0, 1/((1 + (alpha*pc)**n_index)**((n_index - 1)/n_index)), 1)
+#
+# # S-pc-relation ship. We use the van Genuchten approach, i.e. pc = 1/alpha*(S^{-1/m} -1)^1/n, where
+# # we set alpha = 0, assume m = 1-1/n (see Helmig) and assume that residual saturation is Sw
+# def saturation_sym(pc, n_index, alpha):
+#     # inverse capillary pressure-saturation-relationship
+#     #df.conditional(pc > 0,
+#     return 1/((1 + (alpha*pc)**n_index)**((n_index - 1)/n_index))
+#
+#
+# # derivative of S-pc relationship with respect to pc. This is needed for the
+# # construction of a analytic solution.
+# def saturation_sym_prime(pc, n_index, alpha):
+#     # inverse capillary pressure-saturation-relationship
+#     return -(alpha*(n_index - 1)*(alpha*pc)**(n_index - 1)) / ( (1 + (alpha*pc)**n_index)**((2*n_index - 1)/n_index) )
+#
+# derivative of S-pc relationship with respect to pc. This is needed for the
+# construction of a analytic solution.
+
+#
+# # 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, n_index=3, alpha=0.001),
+#     2: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     3: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     4: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     5: ft.partial(saturation_sym, n_index=3, alpha=0.001),
+#     6: ft.partial(saturation_sym, n_index=3, alpha=0.001)
+# }
+#
+# S_pc_sym_prime = {
+#     1: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     2: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     3: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     4: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     5: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001),
+#     6: ft.partial(saturation_sym_prime, n_index=3, alpha=0.001)
+# }
+#
+# sat_pressure_relationship = {
+#     1: ft.partial(saturation, n_index=3, alpha=0.001),
+#     2: ft.partial(saturation, n_index=3, alpha=0.001),
+#     3: ft.partial(saturation, n_index=3, alpha=0.001),
+#     4: ft.partial(saturation, n_index=3, alpha=0.001),
+#     5: ft.partial(saturation, n_index=3, alpha=0.001),
+#     6: ft.partial(saturation, n_index=3, alpha=0.001)
+# }
+
+def saturation(pc, n_index):
+    # inverse capillary pressure-saturation-relationship
+    return df.conditional(pc > 0, 1/((1 + pc)**(1/(n_index + 1))), 1)
+
+
+def saturation_sym(pc, n_index):
+    # inverse capillary pressure-saturation-relationship
+    return 1/((1 + pc)**(1/(n_index + 1)))
+
+def saturation_sym_prime(pc, n_index):
+    # inverse capillary pressure-saturation-relationship
+    return -1/((n_index+1)*(1 + pc)**((n_index+2)/(n_index+1)))
+
+
+S_pc_sym = {
+    1: ft.partial(saturation_sym, n_index=1),
+    2: ft.partial(saturation_sym, n_index=1),
+    3: ft.partial(saturation_sym, n_index=2),
+    4: ft.partial(saturation_sym, n_index=2),
+    5: ft.partial(saturation_sym, n_index=2),
+    6: ft.partial(saturation_sym, n_index=2)
+}
+
+S_pc_sym_prime = {
+    1: ft.partial(saturation_sym_prime, n_index=1),
+    2: ft.partial(saturation_sym_prime, n_index=1),
+    3: ft.partial(saturation_sym_prime, n_index=2),
+    4: ft.partial(saturation_sym_prime, n_index=2),
+    5: ft.partial(saturation_sym_prime, n_index=2),
+    6: ft.partial(saturation_sym_prime, n_index=2)
+}
+
+sat_pressure_relationship = {
+    1: ft.partial(saturation, n_index=1),
+    2: ft.partial(saturation, n_index=1),
+    3: ft.partial(saturation, n_index=2),
+    4: ft.partial(saturation, n_index=2),
+    5: ft.partial(saturation, n_index=2),
+    6: ft.partial(saturation, n_index=2)
+}
+
+
+#############################################
+# 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': -5.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
+        'nonwetting': (-1 -t*(1.1 + y + x**2)) },
+    2: {'wetting': -5.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
+        'nonwetting': (-1 -t*(1.1 + y + x**2)) },
+    3: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    4: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    5: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    6: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    # 2: {'wetting': 1.0 - (1.0 + t*t)*(10.0 + x*x + (y-5.0)*(y-5.0)),
+    #     'nonwetting': - 2 - t*(1 + (y-5.0) + x**2)**2 -sym.sqrt(2+t**2)*(1 + (y-5.0))},
+    # 3: {'wetting': 1.0 - (1.0 + t*t)*(10.0 + x*x + (y-5.0)*(y-5.0)*3*sym.sin(-2*t+2*x)*sym.sin(1/2*y-1.2*t)),
+    #     'nonwetting': - 2 - t*(1 + x**2)**2 -sym.sqrt(2+t**2)},
+    # 4: {'wetting': 1.0 - (1.0 + t*t)*(10.0 + x*x + (y-5.0)*(y-5.0)*3*sym.sin(-2*t+2*x)*sym.sin(1/2*y-1.2*t)),
+    #     'nonwetting': - 2 - t*(1 + x**2)**2 -sym.sqrt(2+t**2)}
+}
+
+# pc_e_sym = {
+#     1: p_e_sym[1]['nonwetting'] - p_e_sym[1]['wetting'],
+#     2: p_e_sym[2]['nonwetting'] - p_e_sym[2]['wetting'],
+#     3: p_e_sym[3]['nonwetting'] - p_e_sym[3]['wetting'],
+#     4: p_e_sym[4]['nonwetting'] - p_e_sym[4]['wetting'],
+#     5: p_e_sym[5]['nonwetting'] - p_e_sym[5]['wetting'],
+#     6: p_e_sym[5]['nonwetting'] - p_e_sym[6]['wetting']
+# }
+
+# pc_e_sym = {
+#     1: -p_e_sym[1]['wetting'],
+#     2: -p_e_sym[2]['wetting'],
+#     3: -p_e_sym[3]['wetting'],
+#     4: -p_e_sym[4]['wetting'],
+#     5: -p_e_sym[5]['wetting'],
+#     6: -p_e_sym[6]['wetting']
+# }
+
+
+pc_e_sym = dict()
+for subdomain, isR in isRichards.items():
+    if isR:
+        pc_e_sym.update({subdomain: -p_e_sym[subdomain]['wetting']})
+    else:
+        pc_e_sym.update({subdomain: p_e_sym[subdomain]['nonwetting']
+                                        - p_e_sym[subdomain]['wetting']})
+
+
+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,
+                        )
+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()
+# similarly to the outer boundary dictionary, if a patch has no outer boundary
+# None should be written instead of an expression.
+# This is a bit of a brainfuck:
+# dirichletBC[ind] gives a dictionary of the outer boundaries of subdomain ind.
+# Since a domain patch can have several disjoint outer boundary parts, the
+# expressions need to get an enumaration index which starts at 0.
+# So dirichletBC[ind][j] is the dictionary of outer dirichlet conditions of
+# subdomain ind and boundary part j.
+# Finally, dirichletBC[ind][j]['wetting'] and dirichletBC[ind][j]['nonwetting']
+# return the actual expression needed for the dirichlet condition for both
+# phases if present.
+
+# subdomain index: {outer boudary part index: {phase: expression}}
+for subdomain in isRichards.keys():
+    # if subdomain has no outer boundary, outer_boundary_def_points[subdomain] is None
+    if outer_boundary_def_points[subdomain] is None:
+        dirichletBC.update({subdomain: None})
+    else:
+        dirichletBC.update({subdomain: dict()})
+        # set the dirichlet conditions to be the same code as exact solution on
+        # the subdomain.
+        for outer_boundary_ind in outer_boundary_def_points[subdomain].keys():
+            dirichletBC[subdomain].update(
+                {outer_boundary_ind: exact_solution[subdomain]}
+                )
+
+write_to_file = {
+    'meshes_and_markers': True,
+    'L_iterations': True
+}
+
+# initialise LDD simulation class
+simulation = ldd.LDDsimulation(tol=1E-14, debug=debugflag, LDDsolver_tol=solver_tol)
+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,
+                          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,
+                          saturation=sat_pressure_relationship,
+                          starttime=starttime,
+                          number_of_timesteps=number_of_timesteps,
+                          number_of_timesteps_to_analyse=number_of_timesteps_to_analyse,
+                          timestep_size=timestep_size,
+                          sources=source_expression,
+                          initial_conditions=initial_condition,
+                          dirichletBC_expression_strings=dirichletBC,
+                          exact_solution=exact_solution,
+                          densities=densities,
+                          include_gravity=include_gravity,
+                          write2file=write_to_file,
+                          )
+
+simulation.initialise()
+# print(simulation.__dict__)
+simulation.run(analyse_condition=analyse_condition)
+# simulation.LDDsolver(time=0, debug=True, analyse_timestep=True)
+# df.info(parameters, True)
diff --git a/TP-TP-layered-soil-case-with-inner-patch/TP-TP-layered_soil_with_inner_patch.py b/TP-TP-layered-soil-case-with-inner-patch/TP-TP-layered_soil_with_inner_patch.py
index 126c91e..1e5e0a6 100755
--- a/TP-TP-layered-soil-case-with-inner-patch/TP-TP-layered_soil_with_inner_patch.py
+++ b/TP-TP-layered-soil-case-with-inner-patch/TP-TP-layered_soil_with_inner_patch.py
@@ -22,26 +22,26 @@ import helpers as hlp
 sym.init_printing()
 
 use_case = "TP-TP-layered-soil-with-inner-patch"
-solver_tol = 5E-7
+solver_tol = 1E-6
 
 ############ GRID #######################ü
-mesh_resolution = 40
+mesh_resolution = 50
 timestep_size = 0.001
 number_of_timesteps = 1500
 # 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 = 5
+number_of_timesteps_to_analyse = 10
 starttime = 0
 
 Lw = 0.25  #/timestep_size
 Lnw=Lw
 
-l_param_w = 40
-l_param_nw = 40
+lambda_w = 41
+lambda_nw = 41
 
-include_gravity = False
+include_gravity = True
 debugflag = False
-analyse_condition = True
+analyse_condition = False
 
 output_string = "./output/nondirichlet_number_of_timesteps{}_".format(number_of_timesteps)
 
@@ -370,18 +370,18 @@ L = {
 
 # subdom_num : lambda parameter for the L-scheme
 lambda_param = {
-    1: {'wetting': l_param_w,
-         'nonwetting': l_param_nw},#
-    2: {'wetting': l_param_w,
-         'nonwetting': l_param_nw},#
-    3: {'wetting': l_param_w,
-         'nonwetting': l_param_nw},#
-    4: {'wetting': l_param_w,
-         'nonwetting': l_param_nw},#
-    5: {'wetting': l_param_w,
-         'nonwetting': l_param_nw},#
-    6: {'wetting': l_param_w,
-         'nonwetting': l_param_nw},#
+    1: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+    2: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+    3: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+    4: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+    5: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
+    6: {'wetting': lambda_w,
+         'nonwetting': lambda_nw},#
 }
 
 
@@ -595,18 +595,18 @@ t = sym.symbols('t', positive=True)
 
 
 p_e_sym = {
-    1: {'wetting': -3.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
-        'nonwetting': (-1 -t*(1-y - x**2)**2) },
-    2: {'wetting': -3.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
-        'nonwetting': (-1 -t*(1-y - x**2)**2) },
-    3: {'wetting': (-3.0 - (1.0 + t*t)*(1.0 + x*x)),
-        'nonwetting': (-1 -t*(1- x**2)**2 - sym.sqrt(2+t**2)*(1+y)*y**2) },
-    4: {'wetting': (-3.0 - (1.0 + t*t)*(1.0 + x*x)),
-        'nonwetting': (-1 -t*(1- x**2)**2 - sym.sqrt(2+t**2)*(1+y)*y**2) },
-    5: {'wetting': (-3.0 - (1.0 + t*t)*(1.0 + x*x)),
-        'nonwetting': (-1 -t*(1- x**2)**2 - sym.sqrt(2+t**2)*(1+y)*y**2) },
-    6: {'wetting': (-3.0 - (1.0 + t*t)*(1.0 + x*x)),
-        'nonwetting': (-1 -t*(1- x**2)**2 - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    1: {'wetting': -5.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
+        'nonwetting': (-1 -t*(1.1 + y + x**2)) },
+    2: {'wetting': -5.0 - (1.0 + t*t)*(1.0 + x*x + y*y),
+        'nonwetting': (-1 -t*(1.1 + y + x**2)) },
+    3: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    4: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    5: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
+    6: {'wetting': (-5.0 - (1.0 + t*t)*(1.0 + x*x)),
+        'nonwetting': (-1 -t*(1 + x**2) - sym.sqrt(2+t**2)*(1+y)*y**2) },
     # 2: {'wetting': 1.0 - (1.0 + t*t)*(10.0 + x*x + (y-5.0)*(y-5.0)),
     #     'nonwetting': - 2 - t*(1 + (y-5.0) + x**2)**2 -sym.sqrt(2+t**2)*(1 + (y-5.0))},
     # 3: {'wetting': 1.0 - (1.0 + t*t)*(10.0 + x*x + (y-5.0)*(y-5.0)*3*sym.sin(-2*t+2*x)*sym.sin(1/2*y-1.2*t)),
-- 
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