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trixi-framework
GitHub Repository: trixi-framework/Trixi.jl
Path: blob/main/examples/p4est_2d_dgsem/elixir_euler_free_stream.jl
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using OrdinaryDiffEqLowStorageRK
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using Trixi
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###############################################################################
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# semidiscretization of the compressible Euler equations
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equations = CompressibleEulerEquations2D(1.4)
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initial_condition = initial_condition_constant
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# Up to version 0.13.0, `max_abs_speed_naive` was used as the default wave speed estimate of
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# `const flux_lax_friedrichs = FluxLaxFriedrichs(), i.e., `FluxLaxFriedrichs(max_abs_speed = max_abs_speed_naive)`.
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# In the `StepsizeCallback`, though, the less diffusive `max_abs_speeds` is employed which is consistent with `max_abs_speed`.
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# Thus, we exchanged in PR#2458 the default wave speed used in the LLF flux to `max_abs_speed`.
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# To ensure that every example still runs we specify explicitly `FluxLaxFriedrichs(max_abs_speed_naive)`.
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# We remark, however, that the now default `max_abs_speed` is in general recommended due to compliance with the
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# `StepsizeCallback` (CFL-Condition) and less diffusion.
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solver = DGSEM(polydeg = 3, surface_flux = FluxLaxFriedrichs(max_abs_speed_naive))
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# Mapping as described in https://arxiv.org/abs/2012.12040 but reduced to 2D
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function mapping(xi_, eta_)
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# Transform input variables between -1 and 1 onto [0,3]
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xi = 1.5 * xi_ + 1.5
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eta = 1.5 * eta_ + 1.5
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y = eta + 3 / 8 * (cos(1.5 * pi * (2 * xi - 3) / 3) *
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cos(0.5 * pi * (2 * eta - 3) / 3))
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x = xi + 3 / 8 * (cos(0.5 * pi * (2 * xi - 3) / 3) *
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cos(2 * pi * (2 * y - 3) / 3))
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return SVector(x, y)
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end
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###############################################################################
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# Get the uncurved mesh from a file (downloads the file if not available locally)
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# Unstructured mesh with 48 cells of the square domain [-1, 1]^n
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mesh_file = Trixi.download("https://gist.githubusercontent.com/efaulhaber/a075f8ec39a67fa9fad8f6f84342cbca/raw/a7206a02ed3a5d3cadacd8d9694ac154f9151db7/square_unstructured_1.inp",
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joinpath(@__DIR__, "square_unstructured_1.inp"))
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# Map the unstructured mesh with the mapping above
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mesh = P4estMesh{2}(mesh_file, polydeg = 3, mapping = mapping, initial_refinement_level = 1)
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# Refine bottom left quadrant of each tree to level 2
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function refine_fn(p4est, which_tree, quadrant)
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quadrant_obj = unsafe_load(quadrant)
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if quadrant_obj.x == 0 && quadrant_obj.y == 0 && quadrant_obj.level < 3
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# return true (refine)
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return Cint(1)
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else
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# return false (don't refine)
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return Cint(0)
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end
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end
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# Refine recursively until each bottom left quadrant of a tree has level 2.
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# The mesh will be rebalanced before the simulation starts.
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refine_fn_c = @cfunction(refine_fn, Cint,
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(Ptr{Trixi.p4est_t}, Ptr{Trixi.p4est_topidx_t},
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Ptr{Trixi.p4est_quadrant_t}))
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Trixi.refine_p4est!(mesh.p4est, true, refine_fn_c, C_NULL)
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semi = SemidiscretizationHyperbolic(mesh, equations, initial_condition, solver,
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boundary_conditions = Dict(:all => BoundaryConditionDirichlet(initial_condition)))
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###############################################################################
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# ODE solvers, callbacks etc.
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tspan = (0.0, 1.0)
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ode = semidiscretize(semi, tspan)
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summary_callback = SummaryCallback()
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analysis_interval = 100
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analysis_callback = AnalysisCallback(semi, interval = analysis_interval)
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alive_callback = AliveCallback(analysis_interval = analysis_interval)
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save_solution = SaveSolutionCallback(interval = 100,
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save_initial_solution = true,
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save_final_solution = true,
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solution_variables = cons2prim)
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stepsize_callback = StepsizeCallback(cfl = 2.0)
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callbacks = CallbackSet(summary_callback,
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analysis_callback, alive_callback,
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save_solution,
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stepsize_callback)
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###############################################################################
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# run the simulation
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sol = solve(ode, CarpenterKennedy2N54(williamson_condition = false);
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dt = 1.0, # solve needs some value here but it will be overwritten by the stepsize_callback
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ode_default_options()..., callback = callbacks);
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