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trixi-framework
GitHub Repository: trixi-framework/Trixi.jl
Path: blob/main/examples/tree_1d_dgsem/elixir_euler_source_terms.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 = CompressibleEulerEquations1D(1.4)
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initial_condition = initial_condition_convergence_test
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# Note that the expected EOC of 5 is not reached with this flux.
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# Using `flux_hll` instead yields the expected EOC.
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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 = 4, surface_flux = FluxLaxFriedrichs(max_abs_speed_naive))
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coordinates_min = 0.0
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coordinates_max = 2.0
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mesh = TreeMesh(coordinates_min, coordinates_max,
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initial_refinement_level = 4,
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n_cells_max = 10_000)
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semi = SemidiscretizationHyperbolic(mesh, equations, initial_condition, solver,
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source_terms = source_terms_convergence_test)
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###############################################################################
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# ODE solvers, callbacks etc.
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tspan = (0.0, 2.0)
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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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extra_analysis_errors = (:l2_error_primitive,
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:linf_error_primitive))
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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 = 0.8)
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time_series = TimeSeriesCallback(semi, [0.0, 0.33, 1.0], interval = 10)
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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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time_series,
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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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