trixi-framework · ranocha · Nov 12, 2023 · Nov 4, 2023 · Nov 7, 2023 · Nov 8, 2023
diff --git a/NEWS.md b/NEWS.md
@@ -4,6 +4,30 @@ Trixi.jl follows the interpretation of [semantic versioning (semver)](https://ju
 used in the Julia ecosystem. Notable changes will be documented in this file
 for human readability.
 
+## Changes when updating to v0.6 from v0.5.x
+
+#### Added
+
+#### Changed
+
+- The wave speed estimates for `flux_hll`, `FluxHLL()` are now consistent across equations.
+  In particular, the functions `min_max_speed_naive`, `min_max_speed_einfeldt` are now 
+  conceptually identical across equations.
+  Users, who have been using `flux_hll` for MHD have now to use `flux_hlle` in order to use the
+  Einfeldt wave speed estimate.
+- Parabolic diffusion terms are now officially supported and not marked as experimental
+  anymore.
+
+#### Deprecated
+
+#### Removed
+
+- The neural network-based shock indicators have been migrated to a new repository
+  [TrixiSmartShockFinder.jl](https://github.com/trixi-framework/TrixiSmartShockFinder.jl).
+  To continue using the indicators, you will need to use both Trixi.jl and
+  TrixiSmartShockFinder.jl, as explained in the latter packages' `README.md`.
+
+
 ## Changes in the v0.5 lifecycle
 
 #### Added
@@ -16,6 +40,7 @@ for human readability.
 - Implementation of the quasi-1D shallow water equations
 - Subcell positivity limiting support for conservative variables in 2D for `TreeMesh`
 - AMR for hyperbolic-parabolic equations on 2D/3D `TreeMesh`
+- Added `GradientVariables` type parameter to `AbstractEquationsParabolic`
 
 #### Changed
 
@@ -32,6 +57,9 @@ for human readability.
 
 #### Removed
 
+- Migrate neural network-based shock indicators to a new repository
+  [TrixiSmartShockFinder.jl](https://github.com/trixi-framework/TrixiSmartShockFinder.jl).
+
 
 ## Changes when updating to v0.5 from v0.4.x
 

diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "Trixi"
 uuid = "a7f1ee26-1774-49b1-8366-f1abc58fbfcb"
 authors = ["Michael Schlottke-Lakemper <[email protected]>", "Gregor Gassner <[email protected]>", "Hendrik Ranocha <[email protected]>", "Andrew R. Winters <[email protected]>", "Jesse Chan <[email protected]>"]
-version = "0.5.49-pre"
+version = "0.6.0"
 
 [deps]
 CodeTracking = "da1fd8a2-8d9e-5ec2-8556-3022fb5608a2"

diff --git a/README.md b/README.md
@@ -18,7 +18,7 @@
   <img width="300px" src="https://trixi-framework.github.io/assets/logo.png">
 </p>
 
-**Trixi.jl** is a numerical simulation framework for hyperbolic conservation
+**Trixi.jl** is a numerical simulation framework for conservation
 laws written in [Julia](https://julialang.org). A key objective for the
 framework is to be useful to both scientists and students. Therefore, next to
 having an extensible design with a fast implementation, Trixi.jl is
@@ -46,6 +46,7 @@ installation and postprocessing procedures. Its features include:
 * Periodic and weakly-enforced boundary conditions
 * Multiple governing equations:
   * Compressible Euler equations
+  * Compressible Navier-Stokes equations
   * Magnetohydrodynamics (MHD) equations
   * Multi-component compressible Euler and MHD equations
   * Linearized Euler and acoustic perturbation equations
@@ -56,6 +57,7 @@ installation and postprocessing procedures. Its features include:
 * Multi-physics simulations
   * [Self-gravitating gas dynamics](https://github.com/trixi-framework/paper-self-gravitating-gas-dynamics)
 * Shared-memory parallelization via multithreading
+* Multi-node parallelization via MPI
 * Visualization and postprocessing of the results
   * In-situ and a posteriori visualization with [Plots.jl](https://github.com/JuliaPlots/Plots.jl)
   * Interactive visualization with [Makie.jl](https://makie.juliaplots.org/)

diff --git a/docs/literate/src/files/DGMulti_1.jl b/docs/literate/src/files/DGMulti_1.jl
@@ -168,7 +168,7 @@ meshIO = StartUpDG.triangulate_domain(StartUpDG.RectangularDomainWithHole());
 
 # The pre-defined Triangulate geometry in StartUpDG has integer boundary tags. With [`DGMultiMesh`](@ref)
 # we assign boundary faces based on these integer boundary tags and create a mesh compatible with Trixi.jl.
-mesh = DGMultiMesh(meshIO, dg, Dict(:outer_boundary=>1, :inner_boundary=>2))
+mesh = DGMultiMesh(dg, meshIO, Dict(:outer_boundary=>1, :inner_boundary=>2))
 #-
 boundary_condition_convergence_test = BoundaryConditionDirichlet(initial_condition)
 boundary_conditions = (; :outer_boundary => boundary_condition_convergence_test,

diff --git a/docs/literate/src/files/adding_new_parabolic_terms.jl b/docs/literate/src/files/adding_new_parabolic_terms.jl
@@ -18,8 +18,15 @@ equations_hyperbolic = LinearScalarAdvectionEquation2D(advection_velocity);
 # `ConstantAnisotropicDiffusion2D` has a field for `equations_hyperbolic`. It is useful to have
 # information about the hyperbolic system available to the parabolic part so that we can reuse
 # functions defined for hyperbolic equations (such as `varnames`).
-
-struct ConstantAnisotropicDiffusion2D{E, T} <: Trixi.AbstractEquationsParabolic{2, 1}
+#
+# The abstract type `Trixi.AbstractEquationsParabolic` has three parameters: `NDIMS` (the spatial dimension,
+# e.g., 1D, 2D, or 3D), `NVARS` (the number of variables), and `GradientVariable`, which we set as
+# `GradientVariablesConservative`. This indicates that the gradient should be taken with respect to the
+# conservative variables (e.g., the same variables used in `equations_hyperbolic`). Users can also take
+# the gradient with respect to a different set of variables; see, for example, the implementation of
+# [`CompressibleNavierStokesDiffusion2D`](@ref), which can utilize either "primitive" or "entropy" variables.
+
+struct ConstantAnisotropicDiffusion2D{E, T} <: Trixi.AbstractEquationsParabolic{2, 1, GradientVariablesConservative}
   diffusivity::T
   equations_hyperbolic::E
 end

diff --git a/docs/src/index.md b/docs/src/index.md
@@ -12,7 +12,7 @@
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3996439.svg)](https://doi.org/10.5281/zenodo.3996439)
 
 [**Trixi.jl**](https://github.com/trixi-framework/Trixi.jl)
-is a numerical simulation framework for hyperbolic conservation
+is a numerical simulation framework for conservation
 laws written in [Julia](https://julialang.org). A key objective for the
 framework is to be useful to both scientists and students. Therefore, next to
 having an extensible design with a fast implementation, Trixi.jl is
@@ -40,6 +40,7 @@ installation and postprocessing procedures. Its features include:
 * Periodic and weakly-enforced boundary conditions
 * Multiple governing equations:
   * Compressible Euler equations
+  * Compressible Navier-Stokes equations
   * Magnetohydrodynamics (MHD) equations
   * Multi-component compressible Euler and MHD equations
   * Linearized Euler and acoustic perturbation equations
@@ -50,6 +51,7 @@ installation and postprocessing procedures. Its features include:
 * Multi-physics simulations
   * [Self-gravitating gas dynamics](https://github.com/trixi-framework/paper-self-gravitating-gas-dynamics)
 * Shared-memory parallelization via multithreading
+* Multi-node parallelization via MPI
 * Visualization and postprocessing of the results
   * In-situ and a posteriori visualization with [Plots.jl](https://github.com/JuliaPlots/Plots.jl)
   * Interactive visualization with [Makie.jl](https://makie.juliaplots.org/)

diff --git a/docs/src/overview.md b/docs/src/overview.md
@@ -60,10 +60,9 @@ different features on different mesh types.
 | Flux differencing                                            |          ✅         |             ✅            |               ✅              |          ✅          |               ✅            | [`VolumeIntegralFluxDifferencing`](@ref)
 | Shock capturing                                              |          ✅         |             ✅            |               ✅              |          ✅          |               ❌            | [`VolumeIntegralShockCapturingHG`](@ref)
 | Nonconservative equations                                    |          ✅         |             ✅            |               ✅              |          ✅          |               ✅            | e.g., GLM MHD or shallow water equations
-| Parabolic termsᵇ                                             |          ✅         |             ✅            |               ❌              |          ✅          |               ✅            | e.g., [`CompressibleNavierStokesDiffusion2D`](@ref)
+| Parabolic terms                                              |          ✅         |             ✅            |               ❌              |          ✅          |               ✅            | e.g., [`CompressibleNavierStokesDiffusion2D`](@ref)
 
 ᵃ: quad = quadrilateral, hex = hexahedron
-ᵇ: Parabolic terms do not currently support adaptivity. 
 
 ## Time integration methods
 

diff --git a/examples/p4est_2d_dgsem/elixir_mhd_alfven_wave.jl b/examples/p4est_2d_dgsem/elixir_mhd_alfven_wave.jl
@@ -12,7 +12,9 @@ initial_condition = initial_condition_convergence_test
 
 # Get the DG approximation space
 volume_flux = (flux_central, flux_nonconservative_powell)
-solver = DGSEM(polydeg = 4, surface_flux = (flux_hll, flux_nonconservative_powell),
+solver = DGSEM(polydeg = 4,
+               surface_flux = (flux_hlle,
+                               flux_nonconservative_powell),
                volume_integral = VolumeIntegralFluxDifferencing(volume_flux))
 
 coordinates_min = (0.0, 0.0)

diff --git a/examples/p4est_3d_dgsem/elixir_mhd_alfven_wave_nonconforming.jl b/examples/p4est_3d_dgsem/elixir_mhd_alfven_wave_nonconforming.jl
@@ -10,7 +10,9 @@ equations = IdealGlmMhdEquations3D(5 / 3)
 initial_condition = initial_condition_convergence_test
 
 volume_flux = (flux_hindenlang_gassner, flux_nonconservative_powell)
-solver = DGSEM(polydeg = 3, surface_flux = (flux_hll, flux_nonconservative_powell),
+solver = DGSEM(polydeg = 3,
+               surface_flux = (flux_hlle,
+                               flux_nonconservative_powell),
                volume_integral = VolumeIntegralFluxDifferencing(volume_flux))
 
 coordinates_min = (-1.0, -1.0, -1.0)

diff --git a/examples/structured_3d_dgsem/elixir_mhd_alfven_wave.jl b/examples/structured_3d_dgsem/elixir_mhd_alfven_wave.jl
@@ -10,7 +10,9 @@ equations = IdealGlmMhdEquations3D(5 / 3)
 initial_condition = initial_condition_convergence_test
 
 volume_flux = (flux_central, flux_nonconservative_powell)
-solver = DGSEM(polydeg = 5, surface_flux = (flux_hll, flux_nonconservative_powell),
+solver = DGSEM(polydeg = 5,
+               surface_flux = (flux_hlle,
+                               flux_nonconservative_powell),
                volume_integral = VolumeIntegralFluxDifferencing(volume_flux))
 
 # Create the mesh

diff --git a/examples/t8code_2d_dgsem/elixir_mhd_alfven_wave.jl b/examples/t8code_2d_dgsem/elixir_mhd_alfven_wave.jl
@@ -11,7 +11,7 @@ initial_condition = initial_condition_convergence_test
 
 # Get the DG approximation space
 volume_flux = (flux_central, flux_nonconservative_powell)
-solver = DGSEM(polydeg = 4, surface_flux = (flux_hll, flux_nonconservative_powell),
+solver = DGSEM(polydeg = 4, surface_flux = (flux_hlle, flux_nonconservative_powell),
                volume_integral = VolumeIntegralFluxDifferencing(volume_flux))
 
 coordinates_min = (0.0, 0.0)

diff --git a/examples/tree_1d_dgsem/elixir_euler_blast_wave_neuralnetwork_perssonperaire.jl b/examples/tree_1d_dgsem/elixir_euler_blast_wave_neuralnetwork_perssonperaire.jl