Merge branch 'QuadraticQuadsAbaqus' of github.com:DanielDoehring/Trix…

…i.jl into QuadraticQuadsAbaqus

NEWS.md

@@ -13,7 +13,7 @@ for human readability.
   and [NLsolve.jl](https://github.com/JuliaNLSolvers/NLsolve.jl) ([#2008])
 - `LobattoLegendreBasis` and related datastructures made fully floating-type general,
   enabling calculations with higher than double (`Float64`) precision ([#2128])
-- In 2D, quadratic elements, i.e., 8-node (quadratic) quadrilaterals and 6-node are now supported in standard Abaqus `inp` format ([#2217])
+- In 2D, quadratic elements, i.e., 8-node (quadratic) quadrilaterals are now supported in standard Abaqus `inp` format ([#2217])
 
 ## Changes when updating to v0.9 from v0.8.x
 

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 = "0.9.12-DEV"
+version = "0.9.13-DEV"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"
@@ -108,7 +108,7 @@ StaticArrays = "1.5"
 StrideArrays = "0.1.26"
 StructArrays = "0.6.11"
 SummationByPartsOperators = "0.5.41"
-T8code = "0.7.2"
+T8code = "0.7.4"
 TimerOutputs = "0.5.7"
 Triangulate = "2.2"
 TriplotBase = "0.1"

README.md

@@ -54,6 +54,7 @@ installation and postprocessing procedures. Its features include:
   * Compressible Navier-Stokes equations
   * Magnetohydrodynamics (MHD) equations
   * Multi-component compressible Euler and MHD equations
+  * Multi-ion compressible MHD equations
   * Linearized Euler and acoustic perturbation equations
   * Hyperbolic diffusion equations for elliptic problems
   * Lattice-Boltzmann equations (D2Q9 and D3Q27 schemes)

examples/p4est_2d_dgsem/elixir_navierstokes_SD7003airfoil.jl

@@ -27,6 +27,7 @@ equations_parabolic = CompressibleNavierStokesDiffusion2D(equations, mu = mu(),
     # set the freestream flow parameters such that c_inf = 1.0 => Mach 0.2
     rho_freestream = 1.4
 
+    # Values correspond to `aoa = 4 * pi / 180`
     v1 = 0.19951281005196486 # 0.2 * cos(aoa)
     v2 = 0.01395129474882506 # 0.2 * sin(aoa)
 

examples/t8code_3d_dgsem/elixir_advection_cubed_sphere.jl

@@ -0,0 +1,61 @@
+using OrdinaryDiffEq
+using Trixi
+
+###############################################################################
+# semidiscretization of the linear advection equation
+
+advection_velocity = (0.2, -0.7, 0.5)
+equations = LinearScalarAdvectionEquation3D(advection_velocity)
+
+# 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)
+
+initial_condition = initial_condition_convergence_test
+
+boundary_condition = BoundaryConditionDirichlet(initial_condition)
+boundary_conditions = Dict(:inside => boundary_condition,
+                           :outside => boundary_condition)
+
+# Note that the first argument refers to the level of refinement, unlike in for p4est
+mesh = Trixi.T8codeMeshCubedSphere(5, 3, 0.5, 0.5;
+                                   polydeg = 3, initial_refinement_level = 0)
+
+# A semidiscretization collects data structures and functions for the spatial discretization
+semi = SemidiscretizationHyperbolic(mesh, equations, initial_condition, solver,
+                                    boundary_conditions = boundary_conditions)
+
+###############################################################################
+# ODE solvers, callbacks etc.
+
+# Create ODE problem with time span from 0.0 to 1.0
+tspan = (0.0, 1.0)
+ode = semidiscretize(semi, tspan)
+
+# At the beginning of the main loop, the SummaryCallback prints a summary of the simulation setup
+# and resets the timers
+summary_callback = SummaryCallback()
+
+# The AnalysisCallback allows to analyse the solution in regular intervals and prints the results
+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)
+
+# The StepsizeCallback handles the re-calculation of the maximum Δt after each time step
+stepsize_callback = StepsizeCallback(cfl = 1.2)
+
+# Create a CallbackSet to collect all callbacks such that they can be passed to the ODE solver
+callbacks = CallbackSet(summary_callback, analysis_callback, save_solution,
+                        stepsize_callback)
+
+###############################################################################
+# run the simulation
+
+# OrdinaryDiffEq's `solve` method evolves the solution in time and executes the passed callbacks
+sol = solve(ode, CarpenterKennedy2N54(williamson_condition = false),
+            dt = 1.0, # solve needs some value here but it will be overwritten by the stepsize_callback
+            save_everystep = false, callback = callbacks);
+
+# Print the timer summary
+summary_callback()