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178 changes: 178 additions & 0 deletions LibTrixi.jl/examples/libelixir_tree2d_warm_bubble.jl
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using LibTrixi
using OrdinaryDiffEq
using Trixi

# Warm bubble test case from
# - Wicker, L. J., and Skamarock, W. C. (1998)
# A time-splitting scheme for the elastic equations incorporating
# second-order Runge–Kutta time differencing
# [DOI: 10.1175/1520-0493(1998)126%3C1992:ATSSFT%3E2.0.CO;2](https://doi.org/10.1175/1520-0493(1998)126%3C1992:ATSSFT%3E2.0.CO;2)
# See also
# - Bryan and Fritsch (2002)
# A Benchmark Simulation for Moist Nonhydrostatic Numerical Models
# [DOI: 10.1175/1520-0493(2002)130<2917:ABSFMN>2.0.CO;2](https://doi.org/10.1175/1520-0493(2002)130<2917:ABSFMN>2.0.CO;2)
# - Carpenter, Droegemeier, Woodward, Hane (1990)
# Application of the Piecewise Parabolic Method (PPM) to
# Meteorological Modeling
# [DOI: 10.1175/1520-0493(1990)118<0586:AOTPPM>2.0.CO;2](https://doi.org/10.1175/1520-0493(1990)118<0586:AOTPPM>2.0.CO;2)
struct WarmBubbleSetup
# Physical constants
g::Float64 # gravity of earth
c_p::Float64 # heat capacity for constant pressure (dry air)
c_v::Float64 # heat capacity for constant volume (dry air)
gamma::Float64 # heat capacity ratio (dry air)

function WarmBubbleSetup(; g = 9.81, c_p = 1004.0, c_v = 717.0, gamma = c_p / c_v)
new(g, c_p, c_v, gamma)
end
end

# Initial condition
function (setup::WarmBubbleSetup)(x, t, equations::CompressibleEulerEquations2D)
@unpack g, c_p, c_v = setup

# center of perturbation
center_x = 10000.0
center_z = 2000.0
# radius of perturbation
radius = 2000.0
# distance of current x to center of perturbation
r = sqrt((x[1] - center_x)^2 + (x[2] - center_z)^2)

# perturbation in potential temperature
potential_temperature_ref = 300.0
potential_temperature_perturbation = 0.0
if r <= radius
potential_temperature_perturbation = 2 * cospi(0.5 * r / radius)^2
end
potential_temperature = potential_temperature_ref + potential_temperature_perturbation

# Exner pressure, solves hydrostatic equation for x[2]
exner = 1 - g / (c_p * potential_temperature) * x[2]

# pressure
p_0 = 100_000.0 # reference pressure
R = c_p - c_v # gas constant (dry air)
p = p_0 * exner^(c_p / R)

# temperature
T = potential_temperature * exner

# density
rho = p / (R * T)

v1 = 20.0
v2 = 0.0
E = c_v * T + 0.5 * (v1^2 + v2^2)
return SVector(rho, rho * v1, rho * v2, rho * E)
end

# Source terms
@inline function (setup::WarmBubbleSetup)(u, x, t, equations::CompressibleEulerEquations2D)
@unpack g = setup
rho, _, rho_v2, _ = u
return SVector(zero(eltype(u)), zero(eltype(u)), -g * rho, -g * rho_v2)
end


# The function to create the simulation state needs to be named `init_simstate`
function init_simstate()

###############################################################################
# semidiscretization of the compressible Euler equations
warm_bubble_setup = WarmBubbleSetup()

equations = CompressibleEulerEquations2D(warm_bubble_setup.gamma)

boundary_conditions = (x_neg = boundary_condition_periodic,
x_pos = boundary_condition_periodic,
y_neg = boundary_condition_slip_wall,
y_pos = boundary_condition_slip_wall)

polydeg = 3
basis = LobattoLegendreBasis(polydeg)

# This is a good estimate for the speed of sound in this example.
# Other values between 300 and 400 should work as well.
surface_flux = FluxLMARS(340.0)

volume_flux = flux_kennedy_gruber
volume_integral = VolumeIntegralFluxDifferencing(volume_flux)

solver = DGSEM(basis, surface_flux, volume_integral)

coordinates_min = (0.0, 0.0)
coordinates_max = (20_000.0, 10_000.0)

# Same coordinates as in examples/structured_2d_dgsem/elixir_euler_warm_bubble.jl
# However TreeMesh will generate a 20_000 x 20_000 square domain instead
mesh = TreeMesh(coordinates_min, coordinates_max,
initial_refinement_level = 6,
n_cells_max = 100_000,
periodicity = (true, false))

semi = SemidiscretizationHyperbolic(mesh, equations, warm_bubble_setup, solver,
source_terms = warm_bubble_setup,
boundary_conditions = boundary_conditions)

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

tspan = (0.0, 1000.0) # 1000 seconds final time

ode = semidiscretize(semi, tspan)

summary_callback = SummaryCallback()

analysis_interval = 1000

analysis_callback = AnalysisCallback(semi, interval = analysis_interval,
extra_analysis_errors = (:entropy_conservation_error,))

alive_callback = AliveCallback(analysis_interval = analysis_interval)

save_solution = SaveSolutionCallback(interval = analysis_interval,
save_initial_solution = true,
save_final_solution = true,
output_directory = "out_bubble",
solution_variables = cons2prim)

@inline function Tpot(u, equations::CompressibleEulerEquations2D)
rho, _, _, p = cons2prim(u, equations)
exner = (p / 100_000)^(1-inv(warm_bubble_setup.gamma))
T = p / rho / (warm_bubble_setup.c_p - warm_bubble_setup.c_v)
return T / exner
end
amr_indicator = IndicatorLöhner(semi, variable = Tpot)
amr_controller = ControllerThreeLevel(semi, amr_indicator,
base_level = 4,
med_level = 6, med_threshold = 0.0002,
max_level = 8, max_threshold = 0.0005)
amr_callback = AMRCallback(semi, amr_controller,
interval = 50,
adapt_initial_condition = true,
adapt_initial_condition_only_refine = true)

stepsize_callback = StepsizeCallback(cfl = 1.0)

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

###############################################################################
# create OrdinaryDiffEq's time integrator
integrator = init(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);

###############################################################################
# Create simulation state
simstate = SimulationState(semi, integrator)

return simstate
end