Adding FEniCSx solver to partitioned-heat-equation tutorial (#317)

* adding fenicsx solver to partitioned-heat-equation tutorial

* Delete printStats.py

* cleanup work

* changed README.md

* output reference solution

* Changed output folder

partitioned-heat-conduction/README.md

@@ -1,7 +1,7 @@
 ---
 title: Partitioned heat conduction
 permalink: tutorials-partitioned-heat-conduction.html
-keywords: FEniCS, Nutils, Heat conduction
+keywords: FEniCSx, FEniCS, Nutils, Heat conduction
 summary: We solve a simple heat equation. The domain is partitioned and the coupling is established in a Dirichlet-Neumann fashion.
 ---
 
@@ -25,6 +25,8 @@ This simple case allows us to compare the solution for the partitioned case to a
 
 You can either couple a solver with itself or different solvers with each other. In any case you will need to have preCICE and the python bindings installed on your system.
 
+* FEniCSx. Install [FEniCSx](https://fenicsproject.org/download/) and the [FEniCSx-adapter](https://github.com/precice/fenicsx-adapter). The code is largely based on this [fenics-tutorial](https://github.com/hplgit/fenics-tutorial/blob/master/pub/python/vol1/ft03_heat.py) from [1] and has been adapted to FEniCSx.
+
 * FEniCS. Install [FEniCS](https://fenicsproject.org/download/) and the [FEniCS-adapter](https://github.com/precice/fenics-adapter). The code is largely based on this [fenics-tutorial](https://github.com/hplgit/fenics-tutorial/blob/master/pub/python/vol1/ft03_heat.py) from [1].
 
 * Nutils. Install [Nutils](https://nutils.org/install-nutils.html).
@@ -43,18 +45,18 @@ For choosing whether you want to run the Dirichlet-kind and a Neumann-kind parti
 For running the case, open two terminals run:
 
 ```bash
-cd fenics
+cd fenicsx
 ./run.sh -d
 ```
 
 and
 
 ```bash
-cd fenics
+cd fenicsx
 ./run.sh -n
 ```
 
-If you want to use Nutils for one or both sides of the setup, just `cd nutils`. The FEniCS case also supports parallel runs. Here, you cannot use the `run.sh` script, but must simply execute
+If you want to use FEniCS or Nutils, use `cd fenics`/ `cd nutils` instead of `cd fenicsx`. The FEniCS case also supports parallel runs. Here, you cannot use the `run.sh` script, but must simply execute
 
 ```bash
 mpirun -n <N_PROC> heat.py -d
@@ -66,7 +68,9 @@ You can mix the Nutils and FEniCS solver, if you like. Note that the error for a
 
 ## Visualization
 
-Output is written into the folders `fenics/out` and `nutils`.
+Output is written into the folders `fenicsx/out`, `fenics/out` and `nutils`.
+
+For FEniCSx you can visualize the content with paraview by opening the `*.xdmf` files. The files `Dirichlet.xdmf` and `Neumann.xdmf` correspond to the numerical solution of the Dirichlet, respectively Neumann, problem, while the files with the prefix `ref` correspond to the analytical reference solution.
 
 For FEniCS you can visualize the content with paraview by opening the `*.pvd` files. The files `Dirichlet.pvd` and `Neumann.pvd` correspond to the numerical solution of the Dirichlet, respectively Neumann, problem, while the files with the prefix `ref` correspond to the analytical reference solution, the files with `error` show the error and the files with `ranks` the ranks of the solvers (if executed in parallel).
 

partitioned-heat-conduction/fenicsx/clean.sh

@@ -0,0 +1,6 @@
+#!/bin/sh
+set -e -u
+
+. ../../tools/cleaning-tools.sh
+
+clean_fenics .

partitioned-heat-conduction/fenicsx/errorcomputation.py

@@ -0,0 +1,16 @@
+from ufl import dx
+from dolfinx.fem import assemble_scalar, form
+import numpy as np
+from mpi4py import MPI
+
+
+def compute_errors(u_approx, u_ref, total_error_tol=10 ** -4):
+    mesh = u_ref.function_space.mesh
+
+    # compute total L2 error between reference and calculated solution
+    error_pointwise = form(((u_approx - u_ref) / u_ref) ** 2 * dx)
+    error_total = np.sqrt(mesh.comm.allreduce(assemble_scalar(error_pointwise), MPI.SUM))
+
+    assert (error_total < total_error_tol)
+
+    return error_total

partitioned-heat-conduction/fenicsx/heat.py

@@ -0,0 +1,252 @@
+"""
+The basic example is taken from "Langtangen, Hans Petter, and Anders Logg. Solving PDEs in Python: The FEniCS
+Tutorial I. Springer International Publishing, 2016."
+
+The example code has been extended with preCICE API calls and mixed boundary conditions to allow for a Dirichlet-Neumann
+coupling of two separate heat equations. It also has been adapted to be compatible with FEniCSx.
+
+The original source code can be found on https://jsdokken.com/dolfinx-tutorial/chapter2/heat_code.html.
+
+Heat equation with Dirichlet conditions. (Dirichlet problem)
+  u'= Laplace(u) + f  in the unit square [0,1] x [0,1]
+  u = u_C             on the coupling boundary at x = 1
+  u = u_D             on the remaining boundary
+  u = u_0             at t = 0
+  u = 1 + x^2 + alpha*y^2 + \beta*t
+  f = beta - 2 - 2*alpha
+
+Heat equation with mixed boundary conditions. (Neumann problem)
+  u'= Laplace(u) + f  in the shifted unit square [1,2] x [0,1]
+  du/dn = f_N         on the coupling boundary at x = 1
+  u = u_D             on the remaining boundary
+  u = u_0             at t = 0
+  u = 1 + x^2 + alpha*y^2 + \beta*t
+  f = beta - 2 - 2*alpha
+"""
+
+from __future__ import print_function, division
+from mpi4py import MPI
+from dolfinx.fem import Function, FunctionSpace, Expression, Constant, dirichletbc, locate_dofs_geometrical
+from dolfinx.fem.petsc import LinearProblem
+from dolfinx.io import XDMFFile
+from ufl import TrialFunction, TestFunction, dx, ds, dot, grad, inner, lhs, rhs, FiniteElement, VectorElement
+from fenicsxprecice import Adapter
+from errorcomputation import compute_errors
+from my_enums import ProblemType, DomainPart
+import argparse
+import numpy as np
+from problem_setup import get_geometry
+
+def determine_gradient(V_g, u):
+    """
+    compute flux following http://hplgit.github.io/INF5620/doc/pub/fenics_tutorial1.1/tu2.html#tut-poisson-gradu
+    :param V_g: Vector function space
+    :param u: solution where gradient is to be determined
+    """
+
+    w = TrialFunction(V_g)
+    v = TestFunction(V_g)
+
+    a = inner(w, v) * dx
+    L = inner(grad(u), v) * dx
+    problem = LinearProblem(a, L)
+    return problem.solve()
+
+parser = argparse.ArgumentParser(description="Solving heat equation for simple or complex interface case")
+command_group = parser.add_mutually_exclusive_group(required=True)
+command_group.add_argument("-d", "--dirichlet", help="create a dirichlet problem", dest="dirichlet",
+                           action="store_true")
+command_group.add_argument("-n", "--neumann", help="create a neumann problem", dest="neumann", action="store_true")
+parser.add_argument("-e", "--error-tol", help="set error tolerance", type=float, default=10**-6,)
+
+args = parser.parse_args()
+
+fenics_dt = .1  # time step size
+# Error is bounded by coupling accuracy. In theory we would obtain the analytical solution.
+error_tol = args.error_tol
+
+alpha = 3  # parameter alpha
+beta = 1.3  # parameter beta
+
+if args.dirichlet and not args.neumann:
+    problem = ProblemType.DIRICHLET
+    domain_part = DomainPart.LEFT
+elif args.neumann and not args.dirichlet:
+    problem = ProblemType.NEUMANN
+    domain_part = DomainPart.RIGHT
+
+mesh, coupling_boundary, remaining_boundary = get_geometry(MPI.COMM_WORLD, domain_part)
+
+# Define function space using mesh
+scalar_element = FiniteElement("P", mesh.ufl_cell(), 2)
+vector_element = VectorElement("P", mesh.ufl_cell(), 1)
+V = FunctionSpace(mesh, scalar_element)
+V_g = FunctionSpace(mesh, vector_element)
+W = V_g.sub(0).collapse()[0]
+
+# Define boundary conditions
+
+
+class Expression_u_D:
+    def __init__(self):
+        self.t = 0.0
+
+    def eval(self, x):
+        return np.full(x.shape[1], 1 + x[0] * x[0] + alpha * x[1] * x[1] + beta * self.t)
+
+
+u_D = Expression_u_D()
+u_D_function = Function(V)
+u_D_function.interpolate(u_D.eval)
+
+if problem is ProblemType.DIRICHLET:
+    # Define flux in x direction
+    class Expression_f_N:
+        def __init__(self):
+            pass
+
+        def eval(self, x):
+            return np.full(x.shape[1], 2 * x[0])
+
+    f_N = Expression_f_N()
+    f_N_function = Function(V)
+    f_N_function.interpolate(f_N.eval)
+
+# Define initial value
+u_n = Function(V, name="Temperature")
+u_n.interpolate(u_D.eval)
+
+precice, precice_dt, initial_data = None, 0.0, None
+
+# Initialize the adapter according to the specific participant
+if problem is ProblemType.DIRICHLET:
+    precice = Adapter(MPI.COMM_WORLD, adapter_config_filename="precice-adapter-config-D.json")
+    precice_dt = precice.initialize(coupling_boundary, read_function_space=V, write_object=f_N_function)
+elif problem is ProblemType.NEUMANN:
+    precice = Adapter(MPI.COMM_WORLD, adapter_config_filename="precice-adapter-config-N.json")
+    precice_dt = precice.initialize(coupling_boundary, read_function_space=W, write_object=u_D_function)
+
+dt = Constant(mesh, 0.0)
+dt.value = np.min([fenics_dt, precice_dt])
+
+# Define variational problem
+u = TrialFunction(V)
+v = TestFunction(V)
+
+
+class Expression_f:
+    def __init__(self):
+        self.t = 0.0
+
+    def eval(self, x):
+        return np.full(x.shape[1], beta - 2 - 2 * alpha)
+
+
+f = Expression_f()
+f_function = Function(V)
+F = u * v / dt * dx + dot(grad(u), grad(v)) * dx - (u_n / dt + f_function) * v * dx
+
+dofs_remaining = locate_dofs_geometrical(V, remaining_boundary)
+bcs = [dirichletbc(u_D_function, dofs_remaining)]
+
+coupling_expression = precice.create_coupling_expression()
+read_data = precice.read_data()
+precice.update_coupling_expression(coupling_expression, read_data)
+if problem is ProblemType.DIRICHLET:
+    # modify Dirichlet boundary condition on coupling interface
+    dofs_coupling = locate_dofs_geometrical(V, coupling_boundary)
+    bcs.append(dirichletbc(coupling_expression, dofs_coupling))
+if problem is ProblemType.NEUMANN:
+    # modify Neumann boundary condition on coupling interface, modify weak
+    # form correspondingly
+    F += v * coupling_expression * ds
+
+a, L = lhs(F), rhs(F)
+
+# Time-stepping
+u_np1 = Function(V, name="Temperature")
+t = 0
+
+# reference solution at t=0
+u_ref = Function(V, name="reference")
+u_ref.interpolate(u_D_function)
+
+# Generating output files
+temperature_out = XDMFFile(MPI.COMM_WORLD, f"./output/{precice.get_participant_name()}.xdmf", "w")
+temperature_out.write_mesh(mesh)
+ref_out = XDMFFile(MPI.COMM_WORLD, f"./output/ref{precice.get_participant_name()}.xdmf", "w")
+ref_out.write_mesh(mesh)
+
+# output solution at t=0, n=0
+n = 0
+
+temperature_out.write_function(u_n, t)
+ref_out.write_function(u_ref, t)
+
+u_D.t = t + dt.value
+u_D_function.interpolate(u_D.eval)
+f.t = t + dt.value
+f_function.interpolate(f.eval)
+
+if problem is ProblemType.DIRICHLET:
+    flux = Function(V_g, name="Heat-Flux")
+
+while precice.is_coupling_ongoing():
+
+    # write checkpoint
+    if precice.is_action_required(precice.action_write_iteration_checkpoint()):
+        precice.store_checkpoint(u_n, t, n)
+
+    read_data = precice.read_data()
+
+    # Update the coupling expression with the new read data
+    precice.update_coupling_expression(coupling_expression, read_data)
+
+    dt.value = np.min([fenics_dt, precice_dt])
+
+    linear_problem = LinearProblem(a, L, bcs=bcs)
+    u_np1 = linear_problem.solve()
+
+    # Write data to preCICE according to which problem is being solved
+    if problem is ProblemType.DIRICHLET:
+        # Dirichlet problem reads temperature and writes flux on boundary to Neumann problem
+        flux = determine_gradient(V_g, u_np1)
+        flux_x = Function(W)
+        flux_x.interpolate(flux.sub(0))
+        precice.write_data(flux_x)
+    elif problem is ProblemType.NEUMANN:
+        # Neumann problem reads flux and writes temperature on boundary to Dirichlet problem
+        precice.write_data(u_np1)
+
+    precice_dt = precice.advance(dt.value)
+
+    # roll back to checkpoint
+    if precice.is_action_required(precice.action_read_iteration_checkpoint()):
+        u_cp, t_cp, n_cp = precice.retrieve_checkpoint()
+        u_n.interpolate(u_cp)
+        t = t_cp
+        n = n_cp
+    else:  # update solution
+        u_n.interpolate(u_np1)
+        t += dt.value
+        n += 1
+
+    if precice.is_time_window_complete():
+        u_ref.interpolate(u_D_function)
+        error = compute_errors(u_n, u_ref, total_error_tol=error_tol)
+        print('n = %d, t = %.2f: L2 error on domain = %.3g' % (n, t, error))
+        print('output u^%d and u_ref^%d' % (n, n))
+
+        temperature_out.write_function(u_n, t)
+        ref_out.write_function(u_ref, t)
+
+
+    # Update Dirichlet BC
+    u_D.t = t + dt.value
+    u_D_function.interpolate(u_D.eval)
+    f.t = t + dt.value
+    f_function.interpolate(f.eval)
+
+
+# Hold plot
+precice.finalize()

partitioned-heat-conduction/fenicsx/my_enums.py

@@ -0,0 +1,17 @@
+from enum import Enum
+
+
+class ProblemType(Enum):
+    """
+    Enum defines problem type. Details see above.
+    """
+    DIRICHLET = 1  # Dirichlet problem
+    NEUMANN = 2  # Neumann problem
+
+
+class DomainPart(Enum):
+    """
+    Enum defines which part of the domain [x_left, x_right] x [y_bottom, y_top] we compute.
+    """
+    LEFT = 1  # left part of domain in simple interface case
+    RIGHT = 2  # right part of domain in simple interface case

partitioned-heat-conduction/fenicsx/precice-adapter-config-D.json

@@ -0,0 +1,9 @@
+{
+  "participant_name": "Dirichlet",
+  "config_file_name": "../precice-config.xml",
+  "interface": {
+      "coupling_mesh_name": "Dirichlet-Mesh",
+      "write_data_name": "Heat-Flux",
+      "read_data_name": "Temperature"
+    }
+}

partitioned-heat-conduction/fenicsx/precice-adapter-config-N.json

@@ -0,0 +1,9 @@
+{
+  "participant_name": "Neumann",
+  "config_file_name": "../precice-config.xml",
+  "interface": {
+      "coupling_mesh_name": "Neumann-Mesh",
+      "write_data_name": "Temperature",
+      "read_data_name": "Heat-Flux"
+    }
+}