elixir_euler_positivity.jl

using OrdinaryDiffEqLowStorageRK
using Trixi

###############################################################################
# semidiscretization of the compressible Euler equations

equations = CompressibleEulerEquations1D(1.4)

"""
    initial_condition_sedov_blast_wave(x, t, equations::CompressibleEulerEquations1D)

The Sedov blast wave setup based on Flash
- https://flash.rochester.edu/site/flashcode/user_support/flash_ug_devel/node187.html#SECTION010114000000000000000
"""
function initial_condition_sedov_blast_wave(x, t, equations::CompressibleEulerEquations1D)
    # Set up polar coordinates
    RealT = eltype(x)
    inicenter = SVector(0)
    x_norm = x[1] - inicenter[1]
    r = abs(x_norm)

    # Setup based on https://flash.rochester.edu/site/flashcode/user_support/flash_ug_devel/node187.html#SECTION010114000000000000000
    r0 = 0.21875f0 # = 3.5 * smallest dx (for domain length=4 and max-ref=6)
    # r0 = 0.5 # = more reasonable setup
    E = 1
    p0_inner = 6 * (equations.gamma - 1) * E / (3 * convert(RealT, pi) * r0)
    p0_outer = convert(RealT, 1.0e-5) # = true Sedov setup
    # p0_outer = 1.0e-3 # = more reasonable setup

    # Calculate primitive variables
    rho = 1
    v1 = 0
    p = r > r0 ? p0_outer : p0_inner

    return prim2cons(SVector(rho, v1, p), equations)
end
initial_condition = initial_condition_sedov_blast_wave

# Up to version 0.13.0, `max_abs_speed_naive` was used as the default wave speed estimate of
# `const flux_lax_friedrichs = FluxLaxFriedrichs(), i.e., `FluxLaxFriedrichs(max_abs_speed = max_abs_speed_naive)`.
# In the `StepsizeCallback`, though, the less diffusive `max_abs_speeds` is employed which is consistent with `max_abs_speed`.
# Thus, we exchanged in PR#2458 the default wave speed used in the LLF flux to `max_abs_speed`.
# To ensure that every example still runs we specify explicitly `FluxLaxFriedrichs(max_abs_speed_naive)`.
# We remark, however, that the now default `max_abs_speed` is in general recommended due to compliance with the 
# `StepsizeCallback` (CFL-Condition) and less diffusion.
surface_flux = FluxLaxFriedrichs(max_abs_speed_naive)
volume_flux = flux_ranocha
basis = LobattoLegendreBasis(3)
indicator_sc = IndicatorHennemannGassner(equations, basis,
                                         alpha_max = 0.5,
                                         alpha_min = 0.001,
                                         alpha_smooth = true,
                                         variable = density_pressure)
volume_integral = VolumeIntegralShockCapturingHG(indicator_sc;
                                                 volume_flux_dg = volume_flux,
                                                 volume_flux_fv = surface_flux)
solver = DGSEM(basis, surface_flux, volume_integral)

coordinates_min = (-2.0,)
coordinates_max = (2.0,)
mesh = TreeMesh(coordinates_min, coordinates_max,
                initial_refinement_level = 6,
                n_cells_max = 10_000)

semi = SemidiscretizationHyperbolic(mesh, equations, initial_condition, solver)

###############################################################################
# ODE solvers, callbacks etc.

tspan = (0.0, 4.0)
ode = semidiscretize(semi, tspan)

summary_callback = SummaryCallback()

analysis_interval = 500
analysis_callback = AnalysisCallback(semi, interval = analysis_interval)

alive_callback = AliveCallback(analysis_interval = analysis_interval)

save_solution = SaveSolutionCallback(interval = 100,
                                     save_initial_solution = true,
                                     save_final_solution = true,
                                     solution_variables = cons2prim)

amr_indicator = IndicatorLöhner(semi,
                                variable = density_pressure)
amr_controller = ControllerThreeLevel(semi, amr_indicator,
                                      base_level = 4,
                                      med_level = 0, med_threshold = 0.1, # med_level = current level
                                      max_level = 6, max_threshold = 0.3)
amr_callback = AMRCallback(semi, amr_controller,
                           interval = 2,
                           adapt_initial_condition = true,
                           adapt_initial_condition_only_refine = true)

stepsize_callback = StepsizeCallback(cfl = 0.5)

callbacks = CallbackSet(summary_callback,
                        analysis_callback, alive_callback,
                        save_solution,
                        amr_callback, stepsize_callback)

stage_limiter! = PositivityPreservingLimiterZhangShu(thresholds = (5.0e-6, 5.0e-6),
                                                     variables = (Trixi.density, pressure))

###############################################################################
# run the simulation

sol = solve(ode, CarpenterKennedy2N54(stage_limiter!, williamson_condition = false);
            dt = 1.0, # solve needs some value here but it will be overwritten by the stepsize_callback
            ode_default_options()..., callback = callbacks);