Merge branch 'main' into sc/converters_coupling

docs/src/callbacks.md

@@ -30,6 +30,11 @@ An example elixir using AMR can be found at [`examples/tree_2d_dgsem/elixir_adve
 The [`AnalysisCallback`](@ref) can be used to analyze the numerical solution, e.g. calculate
 errors or user-specified integrals, and print the results to the screen. The results can also be
 saved in a file. An example can be found at [`examples/tree_2d_dgsem/elixir_euler_vortex.jl`](https://github.com/trixi-framework/Trixi.jl/blob/main/examples/tree_2d_dgsem/elixir_euler_vortex.jl).
+Note that the errors (e.g. `L2 error` or `Linf error`) are computed with respect to the initial condition.
+The percentage of the simulation time refers to the ratio of the current time and the final time, i.e. it does
+not consider the maximal number of iterations. So the simulation could finish before 100% are reached.
+Note that, e.g., due to AMR or smaller time step sizes, the simulation can actually take longer than
+the percentage indicates.
 In [Performance metrics of the `AnalysisCallback`](@ref performance-metrics) you can find a detailed
 description of the different performance metrics the `AnalysisCallback` computes.
 

src/callbacks_step/alive.jl

@@ -86,9 +86,15 @@ function (alive_callback::AliveCallback)(integrator)
         println("─"^100)
         println()
     elseif mpi_isroot()
+        t = integrator.t
+        t_initial = first(integrator.sol.prob.tspan)
+        t_final = last(integrator.sol.prob.tspan)
+        sim_time_percentage = (t - t_initial) / (t_final - t_initial) * 100
         runtime_absolute = 1.0e-9 * (time_ns() - alive_callback.start_time)
-        @printf("#timesteps: %6d │ Δt: %.4e │ sim. time: %.4e │ run time: %.4e s\n",
-                integrator.stats.naccept, integrator.dt, integrator.t, runtime_absolute)
+        println(rpad(@sprintf("#timesteps: %6d │ Δt: %.4e │ sim. time: %.4e (%5.3f%%)",
+                              integrator.stats.naccept, integrator.dt, t,
+                              sim_time_percentage), 71) *
+                @sprintf("│ run time: %.4e s", runtime_absolute))
     end
 
     # avoid re-evaluating possible FSAL stages

src/callbacks_step/analysis.jl

@@ -232,6 +232,12 @@ function (analysis_callback::AnalysisCallback)(u_ode, du_ode, integrator, semi)
     @unpack dt, t = integrator
     iter = integrator.stats.naccept
 
+    # Compute the percentage of the simulation that is done
+    t = integrator.t
+    t_initial = first(integrator.sol.prob.tspan)
+    t_final = last(integrator.sol.prob.tspan)
+    sim_time_percentage = (t - t_initial) / (t_final - t_initial) * 100
+
     # Record performance measurements and compute performance index (PID)
     runtime_since_last_analysis = 1.0e-9 * (time_ns() -
                                    analysis_callback.start_time_last_analysis)
@@ -291,8 +297,8 @@ function (analysis_callback::AnalysisCallback)(u_ode, du_ode, integrator, semi)
                     "               " *
                     " └── GC time:    " *
                     @sprintf("%10.8e s (%5.3f%%)", gc_time_absolute, gc_time_percentage))
-        mpi_println(" sim. time:      " * @sprintf("%10.8e", t) *
-                    "               " *
+        mpi_println(rpad(" sim. time:      " *
+                         @sprintf("%10.8e (%5.3f%%)", t, sim_time_percentage), 46) *
                     " time/DOF/rhs!:  " * @sprintf("%10.8e s", runtime_relative))
         mpi_println("                 " * "              " *
                     "               " *

src/solvers/dgsem_tree/dg_2d_parabolic.jl

@@ -935,7 +935,7 @@ end
 # This is because the parabolic fluxes are assumed to be of the form
 #   `du/dt + df/dx = dg/dx + source(x,t)`,
 # where f(u) is the inviscid flux and g(u) is the viscous flux.
-function apply_jacobian_parabolic!(du, mesh::Union{TreeMesh{2}, P4estMesh{2}},
+function apply_jacobian_parabolic!(du, mesh::TreeMesh{2},
                                    equations::AbstractEquationsParabolic, dg::DG, cache)
     @unpack inverse_jacobian = cache.elements
 
@@ -951,4 +951,22 @@ function apply_jacobian_parabolic!(du, mesh::Union{TreeMesh{2}, P4estMesh{2}},
 
     return nothing
 end
+
+function apply_jacobian_parabolic!(du, mesh::P4estMesh{2},
+                                   equations::AbstractEquationsParabolic,
+                                   dg::DG, cache)
+    @unpack inverse_jacobian = cache.elements
+
+    @threaded for element in eachelement(dg, cache)
+        for j in eachnode(dg), i in eachnode(dg)
+            factor = inverse_jacobian[i, j, element]
+
+            for v in eachvariable(equations)
+                du[v, i, j, element] *= factor
+            end
+        end
+    end
+
+    return nothing
+end
 end # @muladd

src/solvers/dgsem_tree/dg_3d_parabolic.jl

@@ -1125,8 +1125,9 @@ end
 # This is because the parabolic fluxes are assumed to be of the form
 #   `du/dt + df/dx = dg/dx + source(x,t)`,
 # where f(u) is the inviscid flux and g(u) is the viscous flux.
-function apply_jacobian_parabolic!(du, mesh::Union{TreeMesh{3}, P4estMesh{3}},
-                                   equations::AbstractEquationsParabolic, dg::DG, cache)
+function apply_jacobian_parabolic!(du, mesh::TreeMesh{3},
+                                   equations::AbstractEquationsParabolic,
+                                   dg::DG, cache)
     @unpack inverse_jacobian = cache.elements
 
     @threaded for element in eachelement(dg, cache)
@@ -1141,4 +1142,22 @@ function apply_jacobian_parabolic!(du, mesh::Union{TreeMesh{3}, P4estMesh{3}},
 
     return nothing
 end
+
+function apply_jacobian_parabolic!(du, mesh::P4estMesh{3},
+                                   equations::AbstractEquationsParabolic,
+                                   dg::DG, cache)
+    @unpack inverse_jacobian = cache.elements
+
+    @threaded for element in eachelement(dg, cache)
+        for k in eachnode(dg), j in eachnode(dg), i in eachnode(dg)
+            factor = inverse_jacobian[i, j, k, element]
+
+            for v in eachvariable(equations)
+                du[v, i, j, k, element] *= factor
+            end
+        end
+    end
+
+    return nothing
+end
 end # @muladd

test/test_parabolic_2d.jl

@@ -260,24 +260,16 @@ isdir(outdir) && rm(outdir, recursive=true)
   @trixi_testset "P4estMesh2D: elixir_advection_diffusion_periodic_curved.jl" begin
     @test_trixi_include(joinpath(examples_dir(), "p4est_2d_dgsem", "elixir_advection_diffusion_periodic_curved.jl"),
       trees_per_dimension = (1, 1), initial_refinement_level = 2, tspan=(0.0, 0.5),
-      l2 = [0.012380458938507371], 
-      linf = [0.10860506906472567]
-    )
-  end
-
-  @trixi_testset "P4estMesh2D: elixir_advection_diffusion_periodic_curved.jl" begin
-    @test_trixi_include(joinpath(examples_dir(), "p4est_2d_dgsem", "elixir_advection_diffusion_periodic_curved.jl"),
-      trees_per_dimension = (1, 1), initial_refinement_level = 2, tspan=(0.0, 0.5),
-      l2 = [0.012380458938507371], 
-      linf = [0.10860506906472567]
+      l2 = [0.006708147442490916], 
+      linf = [0.04807038397976693]
     )
   end
 
   @trixi_testset "P4estMesh2D: elixir_advection_diffusion_nonperiodic_curved.jl" begin
     @test_trixi_include(joinpath(examples_dir(), "p4est_2d_dgsem", "elixir_advection_diffusion_nonperiodic_curved.jl"),
       trees_per_dimension = (1, 1), initial_refinement_level = 2, tspan=(0.0, 0.5),
-      l2 = [0.04933902988507035], 
-      linf = [0.2550261714590271]
+      l2 = [0.00919917034843865], 
+      linf = [0.14186297438393505]
     )
   end