Merge remote-tracking branch 'origin/main' into tm/new_covariant_metrics

Project.toml

@@ -4,6 +4,7 @@ authors = ["Benedict Geihe <[email protected]>", "Tristan Montoya <montoya.tri
 version = "0.1.0-DEV"
 
 [deps]
+HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LoopVectorization = "bdcacae8-1622-11e9-2a5c-532679323890"
 MuladdMacro = "46d2c3a1-f734-5fdb-9937-b9b9aeba4221"
@@ -17,6 +18,7 @@ StrideArrays = "d1fa6d79-ef01-42a6-86c9-f7c551f8593b"
 Trixi = "a7f1ee26-1774-49b1-8366-f1abc58fbfcb"
 
 [compat]
+HDF5 = "0.16.10, 0.17"
 LinearAlgebra = "1"
 LoopVectorization = "0.12.118"
 MuladdMacro = "0.2.2"

examples/elixir_shallowwater_cubed_sphere_shell_EC_projection.jl

@@ -99,7 +99,7 @@ analysis_callback = AnalysisCallback(semi, interval = 10,
 
 # The SaveSolutionCallback allows to save the solution to a file in regular intervals
 save_solution = SaveSolutionCallback(interval = 10,
-                                     solution_variables = cons2prim)
+                                     solution_variables = cons2prim_and_vorticity)
 
 # The StepsizeCallback handles the re-calculation of the maximum Δt after each time step
 stepsize_callback = StepsizeCallback(cfl = 0.7)

examples/elixir_shallowwater_quad_icosahedron_shell_advection.jl

@@ -68,7 +68,7 @@ analysis_callback = AnalysisCallback(semi, interval = 100,
 
 # The SaveSolutionCallback allows to save the solution to a file in regular intervals
 save_solution = SaveSolutionCallback(interval = 100,
-                                     solution_variables = cons2prim)
+                                     solution_variables = cons2prim_and_vorticity)
 
 # The StepsizeCallback handles the re-calculation of the maximum Δt after each time step
 stepsize_callback = StepsizeCallback(cfl = 0.7)

src/TrixiAtmo.jl

@@ -18,6 +18,7 @@ using StaticArrayInterface: static_size
 using LinearAlgebra: norm, dot, det
 using Reexport: @reexport
 using LoopVectorization: @turbo
+using HDF5: HDF5, h5open, attributes, create_dataset, datatype, dataspace
 
 @reexport using StaticArrays: SVector, SMatrix
 
@@ -38,6 +39,7 @@ export flux_chandrashekar, flux_LMARS
 export velocity, waterheight, pressure, energy_total, energy_kinetic, energy_internal,
        lake_at_rest_error, source_terms_lagrange_multiplier,
        clean_solution_lagrange_multiplier!
+export cons2prim_and_vorticity
 export P4estMeshCubedSphere2D, P4estMeshQuadIcosahedron2D, MetricTermsCrossProduct,
        MetricTermsInvariantCurl
 export EARTH_RADIUS, EARTH_GRAVITATIONAL_ACCELERATION,

src/callbacks_step/callbacks_step.jl

@@ -1,3 +1,4 @@
 include("analysis_covariant.jl")
 include("save_solution_covariant.jl")
 include("stepsize_dg2d.jl")
+include("save_solution_2d_manifold_in_3d_cartesian.jl")

src/callbacks_step/save_solution_2d_manifold_in_3d_cartesian.jl

@@ -0,0 +1,181 @@
+@muladd begin
+#! format: noindent
+
+# Convert to another set of variables using a solution_variables function
+function convert_variables(u, solution_variables, mesh::P4estMesh{2},
+                           equations::AbstractEquations{3}, dg, cache)
+    (; contravariant_vectors) = cache.elements
+    # Extract the number of solution variables to be output 
+    # (may be different than the number of conservative variables) 
+    n_vars = length(Trixi.varnames(solution_variables, equations))
+
+    # Allocate storage for output
+    data = Array{eltype(u)}(undef, n_vars, nnodes(dg), nnodes(dg), nelements(dg, cache))
+
+    # Loop over all nodes and convert variables, passing in auxiliary variables
+    Trixi.@threaded for element in eachelement(dg, cache)
+        for j in eachnode(dg), i in eachnode(dg)
+            normal_vector_node = Trixi.get_contravariant_vector(3,
+                                                                contravariant_vectors,
+                                                                i, j, element)
+
+            if applicable(solution_variables, u, normal_vector_node, mesh, equations,
+                          dg,
+                          cache, i, j, element)
+                # The solution_variables function depends on the solution on other nodes, the normal_vector_node, etc.
+                data_node = solution_variables(u, normal_vector_node, mesh, equations,
+                                               dg,
+                                               cache, i, j, element)
+            else
+                # The solution_variables function depends on u_node and equations
+                u_node = Trixi.get_node_vars(u, equations, dg, i, j, element)
+                data_node = solution_variables(u_node, equations)
+            end
+
+            for v in 1:n_vars
+                data[v, i, j, element] = data_node[v]
+            end
+        end
+    end
+    return data
+end
+
+function Trixi.save_solution_file(u, time, dt, timestep,
+                                  mesh::P4estMesh{2},
+                                  equations::AbstractEquations{3}, dg::DG, cache,
+                                  solution_callback,
+                                  element_variables = Dict{Symbol, Any}(),
+                                  node_variables = Dict{Symbol, Any}();
+                                  system = "")
+    @unpack output_directory, solution_variables = solution_callback
+
+    # Filename based on current time step
+    if isempty(system)
+        filename = joinpath(output_directory, @sprintf("solution_%09d.h5", timestep))
+    else
+        filename = joinpath(output_directory,
+                            @sprintf("solution_%s_%09d.h5", system, timestep))
+    end
+
+    # Convert to different set of variables if requested
+    if solution_variables === cons2cons
+        data = u
+        n_vars = nvariables(equations)
+    else
+        data = convert_variables(u, solution_variables, mesh, equations, dg, cache)
+        n_vars = size(data, 1)
+    end
+
+    # Open file (clobber existing content)
+    # TODO: Create a function to do this in Trixi.jl to avoid duplicated code.
+    h5open(filename, "w") do file
+        # Add context information as attributes
+        attributes(file)["ndims"] = ndims(mesh)
+        attributes(file)["equations"] = Trixi.get_name(equations)
+        attributes(file)["polydeg"] = Trixi.polydeg(dg)
+        attributes(file)["n_vars"] = n_vars
+        attributes(file)["n_elements"] = nelements(dg, cache)
+        attributes(file)["mesh_type"] = Trixi.get_name(mesh)
+        attributes(file)["mesh_file"] = splitdir(mesh.current_filename)[2]
+        attributes(file)["time"] = convert(Float64, time) # Ensure that `time` is written as a double precision scalar
+        attributes(file)["dt"] = convert(Float64, dt) # Ensure that `dt` is written as a double precision scalar
+        attributes(file)["timestep"] = timestep
+
+        # Store each variable of the solution data
+        for v in 1:n_vars
+            # Convert to 1D array
+            file["variables_$v"] = vec(data[v, .., :])
+
+            # Add variable name as attribute
+            var = file["variables_$v"]
+            attributes(var)["name"] = varnames(solution_variables, equations)[v]
+        end
+
+        # Store element variables
+        for (v, (key, element_variable)) in enumerate(element_variables)
+            # Add to file
+            file["element_variables_$v"] = element_variable
+
+            # Add variable name as attribute
+            var = file["element_variables_$v"]
+            attributes(var)["name"] = string(key)
+        end
+
+        # Store node variables
+        for (v, (key, node_variable)) in enumerate(node_variables)
+            # Add to file
+            file["node_variables_$v"] = node_variable
+
+            # Add variable name as attribute
+            var = file["node_variables_$v"]
+            attributes(var)["name"] = string(key)
+        end
+    end
+
+    return filename
+end
+
+# Calculate the primitive variables and the relative vorticity at a given node
+@inline function cons2prim_and_vorticity(u, normal_vector,
+                                         mesh::P4estMesh{2},
+                                         equations::AbstractEquations{3},
+                                         dg::DGSEM, cache, i, j, element)
+
+    # compute the vorticity and project onto normal vector
+    vorticity = calc_vorticity_node(u, mesh, equations, dg, cache, i, j, element)
+    relative_vorticity = dot(vorticity, normal_vector) / norm(normal_vector)
+
+    u_node = Trixi.get_node_vars(u, equations, dg, i, j, element)
+
+    # Return th solution variables
+    return SVector(cons2prim(u_node, equations)..., relative_vorticity)
+end
+
+@inline function calc_vorticity_node(u, mesh::P4estMesh{2},
+                                     equations::AbstractEquations{3}, dg::DGSEM, cache,
+                                     i, j, element)
+    (; derivative_matrix) = dg.basis
+    (; contravariant_vectors, inverse_jacobian) = cache.elements
+
+    # Compute gradients in reference space
+    dv1dxi1 = dv1dxi2 = zero(eltype(u))
+    dv2dxi1 = dv2dxi2 = zero(eltype(u))
+    dv3dxi1 = dv3dxi2 = zero(eltype(u))
+    for ii in eachnode(dg)
+        u_node = Trixi.get_node_vars(u, equations, dg, ii, j, element)
+        v1, v2, v3 = velocity(u_node, equations)
+        dv1dxi1 += derivative_matrix[i, ii] * v1
+        dv2dxi1 += derivative_matrix[i, ii] * v2
+        dv3dxi1 += derivative_matrix[i, ii] * v3
+    end
+
+    for jj in eachnode(dg)
+        u_node = Trixi.get_node_vars(u, equations, dg, i, jj, element)
+        v1, v2, v3 = velocity(u_node, equations)
+        dv1dxi2 += derivative_matrix[j, jj] * v1
+        dv2dxi2 += derivative_matrix[j, jj] * v2
+        dv3dxi2 += derivative_matrix[j, jj] * v3
+    end
+
+    # Transform gradients to Cartesian space
+    Ja11, Ja12, Ja13 = Trixi.get_contravariant_vector(1, contravariant_vectors, i, j,
+                                                      element)
+    Ja21, Ja22, Ja23 = Trixi.get_contravariant_vector(2, contravariant_vectors, i, j,
+                                                      element)
+
+    dv1dy = (Ja12 * dv1dxi1 + Ja22 * dv1dxi2) * inverse_jacobian[i, j, element]
+    dv1dz = (Ja13 * dv1dxi1 + Ja23 * dv1dxi2) * inverse_jacobian[i, j, element]
+    dv2dx = (Ja11 * dv2dxi1 + Ja21 * dv2dxi2) * inverse_jacobian[i, j, element]
+    dv2dz = (Ja13 * dv2dxi1 + Ja23 * dv2dxi2) * inverse_jacobian[i, j, element]
+    dv3dx = (Ja11 * dv3dxi1 + Ja21 * dv3dxi2) * inverse_jacobian[i, j, element]
+    dv3dy = (Ja12 * dv3dxi1 + Ja22 * dv3dxi2) * inverse_jacobian[i, j, element]
+
+    # compute the vorticity
+    return SVector(dv3dy - dv2dz, dv1dz - dv3dx, dv2dx - dv1dy)
+end
+
+# Variable names for cons2prim_and_vorticity
+Trixi.varnames(::typeof(cons2prim_and_vorticity), equations::ShallowWaterEquations3D) = (varnames(cons2prim,
+                                                                                                  equations)...,
+                                                                                         "vorticity")
+end