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Add dry air warm bubble test case (#1779)
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* add LMARS flux in 2D

* add dry air warm bubble test case

* get formatting right

* remove +=

* add DOI

* cleaned up variables (naming, scope)

* reduce run time of test case

* Revert "reduce run time of test case"

This reverts commit b6e527b.

* change output folder

* change energy term in LMARS solver to use p_l/r

* add lmars consistency checks

* switched to kennedy gruber flux

* add euler warm bubble elixir to tests

* adapt errors due to change flux

* add warm bubble test with TreeMesh

* fix unit test

* fix format

* adapt polynomial degree and CFL number

* fix format

* adapt tests due to changed parameters

* Update src/equations/compressible_euler_2d.jl

Co-authored-by: Andrew Winters <andrew.ross.winters@liu.se>

* Update src/equations/compressible_euler_2d.jl

Co-authored-by: Andrew Winters <andrew.ross.winters@liu.se>

* Update src/equations/compressible_euler_3d.jl

Co-authored-by: Andrew Winters <andrew.ross.winters@liu.se>

* Update src/equations/compressible_euler_3d.jl

Co-authored-by: Andrew Winters <andrew.ross.winters@liu.se>

* correct test result

* use callable struct to hold parameters

Thanks sloede!

* Update examples/structured_2d_dgsem/elixir_euler_warm_bubble.jl

Co-authored-by: Hendrik Ranocha <ranocha@users.noreply.github.com>

* Update examples/tree_2d_dgsem/elixir_euler_warm_bubble.jl

Co-authored-by: Hendrik Ranocha <ranocha@users.noreply.github.com>

* year of Wicker paper, comment on tspan

[no ci]

* add comment on speed of sound

---------

Co-authored-by: Andrew Winters <andrew.ross.winters@liu.se>
Co-authored-by: Hendrik Ranocha <ranocha@users.noreply.github.com>
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146 changes: 146 additions & 0 deletions examples/structured_2d_dgsem/elixir_euler_warm_bubble.jl
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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

###############################################################################
# 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)

cells_per_dimension = (64, 32)
mesh = StructuredMesh(cells_per_dimension, coordinates_min, coordinates_max)

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",
solution_variables = cons2prim)

stepsize_callback = StepsizeCallback(cfl = 1.0)

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

###############################################################################
# run the simulation
sol = solve(ode, CarpenterKennedy2N54(williamson_condition = false),
maxiters = 1.0e7,
dt = 1.0, # solve needs some value here but it will be overwritten by the stepsize_callback
save_everystep = false, callback = callbacks);

summary_callback()
150 changes: 150 additions & 0 deletions examples/tree_2d_dgsem/elixir_euler_warm_bubble.jl
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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

###############################################################################
# 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 = 10_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",
solution_variables = cons2prim)

stepsize_callback = StepsizeCallback(cfl = 1.0)

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

###############################################################################
# run the simulation
sol = solve(ode, CarpenterKennedy2N54(williamson_condition = false),
maxiters = 1.0e7,
dt = 1.0, # solve needs some value here but it will be overwritten by the stepsize_callback
save_everystep = false, callback = callbacks);

summary_callback()
92 changes: 92 additions & 0 deletions src/equations/compressible_euler_2d.jl
Original file line number Diff line number Diff line change
Expand Up @@ -809,6 +809,98 @@ end
return SVector(f1m, f2m, f3m, f4m)
end

"""
FluxLMARS(c)(u_ll, u_rr, orientation_or_normal_direction,
equations::CompressibleEulerEquations2D)
Low Mach number approximate Riemann solver (LMARS) for atmospheric flows using
an estimate `c` of the speed of sound.
References:
- Xi Chen et al. (2013)
A Control-Volume Model of the Compressible Euler Equations with a Vertical
Lagrangian Coordinate
[DOI: 10.1175/MWR-D-12-00129.1](https://doi.org/10.1175/mwr-d-12-00129.1)
"""
struct FluxLMARS{SpeedOfSound}
# Estimate for the speed of sound
speed_of_sound::SpeedOfSound
end

@inline function (flux_lmars::FluxLMARS)(u_ll, u_rr, orientation::Integer,
equations::CompressibleEulerEquations2D)
c = flux_lmars.speed_of_sound

# Unpack left and right state
rho_ll, v1_ll, v2_ll, p_ll = cons2prim(u_ll, equations)
rho_rr, v1_rr, v2_rr, p_rr = cons2prim(u_rr, equations)

if orientation == 1
v_ll = v1_ll
v_rr = v1_rr
else # orientation == 2
v_ll = v2_ll
v_rr = v2_rr
end

rho = 0.5 * (rho_ll + rho_rr)
p = 0.5 * (p_ll + p_rr) - 0.5 * c * rho * (v_rr - v_ll)
v = 0.5 * (v_ll + v_rr) - 1 / (2 * c * rho) * (p_rr - p_ll)

# We treat the energy term analogous to the potential temperature term in the paper by
# Chen et al., i.e. we use p_ll and p_rr, and not p
if v >= 0
f1, f2, f3, f4 = v * u_ll
f4 = f4 + p_ll * v
else
f1, f2, f3, f4 = v * u_rr
f4 = f4 + p_rr * v
end

if orientation == 1
f2 = f2 + p
else # orientation == 2
f3 = f3 + p
end

return SVector(f1, f2, f3, f4)
end

@inline function (flux_lmars::FluxLMARS)(u_ll, u_rr, normal_direction::AbstractVector,
equations::CompressibleEulerEquations2D)
c = flux_lmars.speed_of_sound

# Unpack left and right state
rho_ll, v1_ll, v2_ll, p_ll = cons2prim(u_ll, equations)
rho_rr, v1_rr, v2_rr, p_rr = cons2prim(u_rr, equations)

v_ll = v1_ll * normal_direction[1] + v2_ll * normal_direction[2]
v_rr = v1_rr * normal_direction[1] + v2_rr * normal_direction[2]

# Note that this is the same as computing v_ll and v_rr with a normalized normal vector
# and then multiplying v by `norm_` again, but this version is slightly faster.
norm_ = norm(normal_direction)

rho = 0.5 * (rho_ll + rho_rr)
p = 0.5 * (p_ll + p_rr) - 0.5 * c * rho * (v_rr - v_ll) / norm_
v = 0.5 * (v_ll + v_rr) - 1 / (2 * c * rho) * (p_rr - p_ll) * norm_

# We treat the energy term analogous to the potential temperature term in the paper by
# Chen et al., i.e. we use p_ll and p_rr, and not p
if v >= 0
f1, f2, f3, f4 = u_ll * v
f4 = f4 + p_ll * v
else
f1, f2, f3, f4 = u_rr * v
f4 = f4 + p_rr * v
end

return SVector(f1,
f2 + p * normal_direction[1],
f3 + p * normal_direction[2],
f4)
end

"""
splitting_vanleer_haenel(u, orientation::Integer,
equations::CompressibleEulerEquations2D)
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