AMR for 1D Parabolic Eqs (Clean branch)

examples/tree_1d_dgsem/elixir_navierstokes_convergence_walls_amr.jl

@@ -0,0 +1,172 @@
+using OrdinaryDiffEq
+using Trixi
+
+###############################################################################
+# semidiscretization of the ideal compressible Navier-Stokes equations
+
+prandtl_number() = 0.72
+mu() = 0.01
+
+equations = CompressibleEulerEquations1D(1.4)
+equations_parabolic = CompressibleNavierStokesDiffusion1D(equations, mu=mu(), Prandtl=prandtl_number(),
+                                                          gradient_variables=GradientVariablesEntropy())
+
+# Create DG solver with polynomial degree = 3 and (local) Lax-Friedrichs/Rusanov flux as surface flux
+solver = DGSEM(polydeg=3, surface_flux=flux_lax_friedrichs,
+               volume_integral=VolumeIntegralWeakForm())
+
+coordinates_min = -1.0
+coordinates_max =  1.0
+
+# Create a uniformly refined mesh with periodic boundaries
+mesh = TreeMesh(coordinates_min, coordinates_max,
+                initial_refinement_level=3,
+                periodicity=false,
+                n_cells_max=30_000) # set maximum capacity of tree data structure
+
+# Note: the initial condition cannot be specialized to `CompressibleNavierStokesDiffusion1D`
+#       since it is called by both the parabolic solver (which passes in `CompressibleNavierStokesDiffusion1D`)
+#       and by the initial condition (which passes in `CompressibleEulerEquations1D`).
+# This convergence test setup was originally derived by Andrew Winters (@andrewwinters5000)
+function initial_condition_navier_stokes_convergence_test(x, t, equations)
+  # Amplitude and shift
+  A = 0.5
+  c = 2.0
+
+  # convenience values for trig. functions
+  pi_x = pi * x[1]
+  pi_t = pi * t
+
+  rho = c + A * cos(pi_x) * cos(pi_t)
+  v1  = log(x[1] + 2.0) * (1.0 - exp(-A * (x[1] - 1.0)) ) * cos(pi_t)
+  p   = rho^2
+
+  return prim2cons(SVector(rho, v1, p), equations)
+end
+
+@inline function source_terms_navier_stokes_convergence_test(u, x, t, equations)
+  x = x[1]
+
+  # TODO: parabolic
+  # we currently need to hardcode these parameters until we fix the "combined equation" issue
+  # see also https://github.com/trixi-framework/Trixi.jl/pull/1160
+  inv_gamma_minus_one = inv(equations.gamma - 1)
+  Pr = prandtl_number()
+  mu_ = mu()
+
+  # Same settings as in `initial_condition`
+  # Amplitude and shift
+  A = 0.5
+  c = 2.0
+
+  # convenience values for trig. functions
+  pi_x = pi * x
+  pi_t = pi * t
+
+  # compute the manufactured solution and all necessary derivatives
+  rho    =  c  + A * cos(pi_x) * cos(pi_t)
+  rho_t  = -pi * A * cos(pi_x) * sin(pi_t)
+  rho_x  = -pi * A * sin(pi_x) * cos(pi_t)
+  rho_xx = -pi * pi * A * cos(pi_x) * cos(pi_t)
+
+  v1    =       log(x + 2.0) * (1.0 - exp(-A * (x - 1.0))) * cos(pi_t)
+  v1_t  = -pi * log(x + 2.0) * (1.0 - exp(-A * (x - 1.0))) * sin(pi_t)
+  v1_x  =       (A * log(x + 2.0) * exp(-A * (x - 1.0)) + (1.0 - exp(-A * (x - 1.0))) / (x + 2.0)) * cos(pi_t)
+  v1_xx = (( 2.0 * A * exp(-A * (x - 1.0)) / (x + 2.0)
+                         - A * A * log(x + 2.0) * exp(-A * (x - 1.0))
+                         - (1.0 - exp(-A * (x - 1.0))) / ((x + 2.0) * (x + 2.0))) * cos(pi_t))
+
+  p    = rho * rho
+  p_t  = 2.0 * rho * rho_t
+  p_x  = 2.0 * rho * rho_x
+  p_xx = 2.0 * rho * rho_xx + 2.0 * rho_x * rho_x
+
+  # Note this simplifies slightly because the ansatz assumes that v1 = v2
+  E   = p * inv_gamma_minus_one + 0.5 * rho * v1^2
+  E_t = p_t * inv_gamma_minus_one + 0.5 * rho_t * v1^2 + rho * v1 * v1_t
+  E_x = p_x * inv_gamma_minus_one + 0.5 * rho_x * v1^2 + rho * v1 * v1_x
+
+  # Some convenience constants
+  T_const = equations.gamma * inv_gamma_minus_one / Pr
+  inv_rho_cubed = 1.0 / (rho^3)
+
+  # compute the source terms
+  # density equation
+  du1 = rho_t + rho_x * v1 + rho * v1_x
+
+  # y-momentum equation
+  du2 = ( rho_t * v1 + rho * v1_t 
+         + p_x + rho_x * v1^2 + 2.0 * rho * v1 * v1_x
+    # stress tensor from y-direction
+         - v1_xx * mu_)
+
+  # total energy equation
+  du3 = ( E_t + v1_x * (E + p) + v1 * (E_x + p_x)
+    # stress tensor and temperature gradient terms from x-direction
+                                - v1_xx * v1   * mu_
+                                - v1_x  * v1_x * mu_
+         - T_const * inv_rho_cubed * (        p_xx * rho   * rho
+                                      - 2.0 * p_x  * rho   * rho_x
+                                      + 2.0 * p    * rho_x * rho_x
+                                      -       p    * rho   * rho_xx ) * mu_ )
+
+  return SVector(du1, du2, du3)
+end
+
+initial_condition = initial_condition_navier_stokes_convergence_test
+
+# BC types
+velocity_bc_left_right = NoSlip((x, t, equations) -> initial_condition_navier_stokes_convergence_test(x, t, equations)[2])
+
+heat_bc_left = Isothermal((x, t, equations) -> 
+                          Trixi.temperature(initial_condition_navier_stokes_convergence_test(x, t, equations), 
+                                            equations_parabolic))
+heat_bc_right = Adiabatic((x, t, equations) -> 0.0)
+
+boundary_condition_left = BoundaryConditionNavierStokesWall(velocity_bc_left_right, heat_bc_left)
+boundary_condition_right = BoundaryConditionNavierStokesWall(velocity_bc_left_right, heat_bc_right)
+
+# define inviscid boundary conditions
+boundary_conditions = (; x_neg = boundary_condition_slip_wall,
+                         x_pos = boundary_condition_slip_wall)
+
+# define viscous boundary conditions
+boundary_conditions_parabolic = (; x_neg = boundary_condition_left,
+                                   x_pos = boundary_condition_right)
+
+semi = SemidiscretizationHyperbolicParabolic(mesh, (equations, equations_parabolic), initial_condition, solver;
+                                             boundary_conditions=(boundary_conditions, boundary_conditions_parabolic),
+                                             source_terms=source_terms_navier_stokes_convergence_test)
+
+###############################################################################
+# ODE solvers, callbacks etc.
+
+# Create ODE problem with time span `tspan`
+tspan = (0.0, 1.0)
+ode = semidiscretize(semi, tspan)
+
+summary_callback = SummaryCallback()
+alive_callback = AliveCallback(alive_interval=10)
+analysis_interval = 100
+analysis_callback = AnalysisCallback(semi, interval=analysis_interval)
+
+amr_controller = ControllerThreeLevel(semi, 
+                                      IndicatorLöhner(semi, variable=Trixi.density),
+                                      base_level=3,
+                                      med_level=4, med_threshold=0.005,
+                                      max_level=5, max_threshold=0.01)
+
+amr_callback = AMRCallback(semi, amr_controller,
+                           interval=5,
+                           adapt_initial_condition=true)
+
+# Create a CallbackSet to collect all callbacks such that they can be passed to the ODE solver
+callbacks = CallbackSet(summary_callback, analysis_callback, alive_callback, amr_callback)
+
+###############################################################################
+# run the simulation
+
+time_int_tol = 1e-8
+sol = solve(ode, RDPK3SpFSAL49(); abstol=time_int_tol, reltol=time_int_tol, dt = 1e-5,
+            ode_default_options()..., callback=callbacks)
+summary_callback() # print the timer summary

src/callbacks_step/amr.jl

@@ -192,6 +192,16 @@ end
     amr_callback(u_ode, mesh_equations_solver_cache(semi)..., semi, t, iter; kwargs...)
 end
 
+@inline function (amr_callback::AMRCallback)(u_ode::AbstractVector,
+                                             semi::SemidiscretizationHyperbolicParabolic,
+                                             t, iter;
+                                             kwargs...)
+    # Note that we don't `wrap_array` the vector `u_ode` to be able to `resize!`
+    # it when doing AMR while still dispatching on the `mesh` etc.
+    amr_callback(u_ode, mesh_equations_solver_cache(semi)..., semi.cache_parabolic,
+                 semi, t, iter; kwargs...)
+end
+
 # `passive_args` is currently used for Euler with self-gravity to adapt the gravity solver
 # passively without querying its indicator, based on the assumption that both solvers use
 # the same mesh. That's a hack and should be improved in the future once we have more examples
@@ -346,6 +356,168 @@ function (amr_callback::AMRCallback)(u_ode::AbstractVector, mesh::TreeMesh,
     return has_changed
 end
 
+# `passive_args` is currently used for Euler with self-gravity to adapt the gravity solver
+# passively without querying its indicator, based on the assumption that both solvers use
+# the same mesh. That's a hack and should be improved in the future once we have more examples
+# and a better understanding of such a coupling.
+# `passive_args` is expected to be an iterable of `Tuple`s of the form
+# `(p_u_ode, p_mesh, p_equations, p_dg, p_cache)`.
+function (amr_callback::AMRCallback)(u_ode::AbstractVector, mesh::TreeMesh,
+                                     equations, dg::DG,
+                                     cache, cache_parabolic,
+                                     semi::SemidiscretizationHyperbolicParabolic,
+                                     t, iter;
+                                     only_refine = false, only_coarsen = false,
+                                     passive_args = ())
+    @unpack controller, adaptor = amr_callback
+
+    u = wrap_array(u_ode, mesh, equations, dg, cache)
+    # TODO: Keep indicator based on hyperbolic variables?
+    lambda = @trixi_timeit timer() "indicator" controller(u, mesh, equations, dg, cache,
+                                                          t = t, iter = iter)
+
+    if mpi_isparallel()
+        # Collect lambda for all elements
+        lambda_global = Vector{eltype(lambda)}(undef, nelementsglobal(dg, cache))
+        # Use parent because n_elements_by_rank is an OffsetArray
+        recvbuf = MPI.VBuffer(lambda_global, parent(cache.mpi_cache.n_elements_by_rank))
+        MPI.Allgatherv!(lambda, recvbuf, mpi_comm())
+        lambda = lambda_global
+    end
+
+    leaf_cell_ids = leaf_cells(mesh.tree)
+    @boundscheck begin
+        @assert axes(lambda)==axes(leaf_cell_ids) ("Indicator (axes = $(axes(lambda))) and leaf cell (axes = $(axes(leaf_cell_ids))) arrays have different axes")
+    end
+
+    @unpack to_refine, to_coarsen = amr_callback.amr_cache
+    empty!(to_refine)
+    empty!(to_coarsen)
+    for element in 1:length(lambda)
+        controller_value = lambda[element]
+        if controller_value > 0
+            push!(to_refine, leaf_cell_ids[element])
+        elseif controller_value < 0
+            push!(to_coarsen, leaf_cell_ids[element])
+        end
+    end
+
+    @trixi_timeit timer() "refine" if !only_coarsen && !isempty(to_refine)
+        # refine mesh
+        refined_original_cells = @trixi_timeit timer() "mesh" refine!(mesh.tree,
+                                                                      to_refine)
+
+        # Find all indices of elements whose cell ids are in refined_original_cells
+        # NOTE: This assumes same indices for hyperbolic and parabolic part!
+        elements_to_refine = findall(in(refined_original_cells),
+                                     cache.elements.cell_ids)
+
+        # refine solver
+        @trixi_timeit timer() "solver" refine!(u_ode, adaptor, mesh, equations, dg,
+                                               cache, cache_parabolic,
+                                               elements_to_refine)
+        for (p_u_ode, p_mesh, p_equations, p_dg, p_cache) in passive_args
+            @trixi_timeit timer() "passive solver" refine!(p_u_ode, adaptor, p_mesh,
+                                                           p_equations, p_dg, p_cache,
+                                                           elements_to_refine)
+        end
+    else
+        # If there is nothing to refine, create empty array for later use
+        refined_original_cells = Int[]
+    end
+
+    @trixi_timeit timer() "coarsen" if !only_refine && !isempty(to_coarsen)
+        # Since the cells may have been shifted due to refinement, first we need to
+        # translate the old cell ids to the new cell ids
+        if !isempty(to_coarsen)
+            to_coarsen = original2refined(to_coarsen, refined_original_cells, mesh)
+        end
+
+        # Next, determine the parent cells from which the fine cells are to be
+        # removed, since these are needed for the coarsen! function. However, since
+        # we only want to coarsen if *all* child cells are marked for coarsening,
+        # we count the coarsening indicators for each parent cell and only coarsen
+        # if all children are marked as such (i.e., where the count is 2^ndims). At
+        # the same time, check if a cell is marked for coarsening even though it is
+        # *not* a leaf cell -> this can only happen if it was refined due to 2:1
+        # smoothing during the preceding refinement operation.
+        parents_to_coarsen = zeros(Int, length(mesh.tree))
+        for cell_id in to_coarsen
+            # If cell has no parent, it cannot be coarsened
+            if !has_parent(mesh.tree, cell_id)
+                continue
+            end
+
+            # If cell is not leaf (anymore), it cannot be coarsened
+            if !is_leaf(mesh.tree, cell_id)
+                continue
+            end
+
+            # Increase count for parent cell
+            parent_id = mesh.tree.parent_ids[cell_id]
+            parents_to_coarsen[parent_id] += 1
+        end
+
+        # Extract only those parent cells for which all children should be coarsened
+        to_coarsen = collect(1:length(parents_to_coarsen))[parents_to_coarsen .== 2^ndims(mesh)]
+
+        # Finally, coarsen mesh
+        coarsened_original_cells = @trixi_timeit timer() "mesh" coarsen!(mesh.tree,
+                                                                         to_coarsen)
+
+        # Convert coarsened parent cell ids to the list of child cell ids that have
+        # been removed, since this is the information that is expected by the solver
+        removed_child_cells = zeros(Int,
+                                    n_children_per_cell(mesh.tree) *
+                                    length(coarsened_original_cells))
+        for (index, coarse_cell_id) in enumerate(coarsened_original_cells)
+            for child in 1:n_children_per_cell(mesh.tree)
+                removed_child_cells[n_children_per_cell(mesh.tree) * (index - 1) + child] = coarse_cell_id +
+                                                                                            child
+            end
+        end
+
+        # Find all indices of elements whose cell ids are in removed_child_cells
+        # NOTE: This assumes same indices for hyperbolic and parabolic part!
+        elements_to_remove = findall(in(removed_child_cells), cache.elements.cell_ids)
+
+        # coarsen solver
+        @trixi_timeit timer() "solver" coarsen!(u_ode, adaptor, mesh, equations, dg,
+                                                cache, cache_parabolic,
+                                                elements_to_remove)
+
+        for (p_u_ode, p_mesh, p_equations, p_dg, p_cache) in passive_args
+            @trixi_timeit timer() "passive solver" coarsen!(p_u_ode, adaptor, p_mesh,
+                                                            p_equations, p_dg, p_cache,
+                                                            elements_to_remove)
+        end
+    else
+        # If there is nothing to coarsen, create empty array for later use
+        coarsened_original_cells = Int[]
+    end
+
+    # Store whether there were any cells coarsened or refined
+    has_changed = !isempty(refined_original_cells) || !isempty(coarsened_original_cells)
+    if has_changed # TODO: Taal decide, where shall we set this?
+        # don't set it to has_changed since there can be changes from earlier calls
+        mesh.unsaved_changes = true
+    end
+
+    # Dynamically balance computational load by first repartitioning the mesh and then redistributing the cells/elements
+    if has_changed && mpi_isparallel() && amr_callback.dynamic_load_balancing
+        @trixi_timeit timer() "dynamic load balancing" begin
+            old_mpi_ranks_per_cell = copy(mesh.tree.mpi_ranks)
+
+            partition!(mesh)
+
+            rebalance_solver!(u_ode, mesh, equations, dg, cache, old_mpi_ranks_per_cell)
+        end
+    end
+
+    # Return true if there were any cells coarsened or refined, otherwise false
+    return has_changed
+end
+
 # Copy controller values to quad user data storage, will be called below
 function copy_to_quad_iter_volume(info, user_data)
     info_pw = PointerWrapper(info)