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Feature: t8code cubed spherical shell setups (#1918)
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* Wrap from_abaqus routines.

* Implement geometry data transfer from t8code to Trixi.

* Updated examples.

* Fixed typos.

* Applied formatter.

* cubed sphere test case, copied from p4est

* add baroclinic instability (copy of p4est)

* add cubed sphere constructor

* Fix indentation.

* Fix indentation.

* Switching off formatter in two files.

* Upgrading T8code.jl.

* Fixed examples.

* stress different meaning of first argument

it refers to level of refinement in lat lon direction, not number of
tree as in the p4est version

* use lat lon levels

* add t8code cubed sphere tests

* Remove TODO comments

* Relaxing T8code.jl version requirement.

* Restricted t8code version requirement.

* Removed cubed spherical shell related code.

* Removed cubed spherical shell tests.

* Including cubed spherical shell setup.

* Modified GH ci such that it uses the latest T8code.jl package.

* Included cubed spherical shell setups and tests.

* Switching order of CI steps.

* Changed line in CI.

* Increasing code coverage.

* Increasing code coverage.

* Further increasing code coverage.

* Re-introduced tests.

* Removed workaround in github workflow.

* Applied formatter.

* adapt to merged t8code PR

* missed calling constructor

* Backup.

* Add save callback to elixir.

* Backup.

* Refined code. Make it work in parallel.

* Added support for parallelt8codemesh save solution callback.

* Applied formatter.

* Updated examples and tests.

* Applied formatter.

* Minor adjustments.

* Code refinement. Enabled partitioning after mesh loading.

* Applied formatter and fixed typos.

* Removed commented out section.

* Added missing union type member.

* Switching from UInt64 to UInt128 in global interface/mortar id computation.

* Switching from UInt64 to UInt128 in global interface/mortar id computation (II).

* Adding more tests.

* Applied formatter.

* Removed Printf.

* Incorporated review comments and code polish.

* Applied formatter.

* Fixed typos.

* Update examples/t8code_2d_dgsem/elixir_advection_restart.jl

Co-authored-by: Joshua Lampert <[email protected]>

* Update examples/t8code_2d_dgsem/elixir_advection_restart_amr.jl

Co-authored-by: Joshua Lampert <[email protected]>

* Update examples/t8code_3d_dgsem/elixir_advection_restart.jl

Co-authored-by: Joshua Lampert <[email protected]>

* Update src/meshes/mesh_io.jl

Co-authored-by: Joshua Lampert <[email protected]>

* Update examples/t8code_3d_dgsem/elixir_advection_restart.jl

Co-authored-by: Joshua Lampert <[email protected]>

* Update src/meshes/t8code_mesh.jl

Co-authored-by: Joshua Lampert <[email protected]>

* Update src/meshes/t8code_mesh.jl

Co-authored-by: Joshua Lampert <[email protected]>

* Removing last test in t8code 2D MPI to investigate problems in Github CI.

* Refactored a bit.

* Applied formatter.

* Removed commented code.

* Added LOG_LEVEL variable.

* Added t8code interface simplfication and stitched memory leak.

* Applied formatter.

* Simplifying finailze behavior for T8codeMesh.

* Addeing finalize call to T8codeMesh examples.

* Applied formatter.

* Update test/test_t8code_3d.jl

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

* Update test/test_t8code_3d.jl

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

* re-add test

* remove duplicate

* Fixing minor stuff.

* bump t8code

* Update test/test_t8code_3d.jl

Co-authored-by: Joshua Lampert <[email protected]>

---------

Co-authored-by: Johannes Markert <[email protected]>
Co-authored-by: Benedict Geihe <[email protected]>
Co-authored-by: Benedict <[email protected]>
Co-authored-by: Joshua Lampert <[email protected]>
Co-authored-by: Hendrik Ranocha <[email protected]>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
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2 changes: 1 addition & 1 deletion Project.toml
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Expand Up @@ -108,7 +108,7 @@ StaticArrays = "1.5"
StrideArrays = "0.1.26"
StructArrays = "0.6.11"
SummationByPartsOperators = "0.5.41"
T8code = "0.7.2"
T8code = "0.7.4"
TimerOutputs = "0.5.7"
Triangulate = "2.2"
TriplotBase = "0.1"
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61 changes: 61 additions & 0 deletions examples/t8code_3d_dgsem/elixir_advection_cubed_sphere.jl
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using OrdinaryDiffEq
using Trixi

###############################################################################
# semidiscretization of the linear advection equation

advection_velocity = (0.2, -0.7, 0.5)
equations = LinearScalarAdvectionEquation3D(advection_velocity)

# Create DG solver with polynomial degree = 3 and (local) Lax-Friedrichs/Rusanov flux as surface flux
solver = DGSEM(polydeg = 3, surface_flux = flux_lax_friedrichs)

initial_condition = initial_condition_convergence_test

boundary_condition = BoundaryConditionDirichlet(initial_condition)
boundary_conditions = Dict(:inside => boundary_condition,
:outside => boundary_condition)

# Note that the first argument refers to the level of refinement, unlike in for p4est
mesh = Trixi.T8codeMeshCubedSphere(5, 3, 0.5, 0.5;
polydeg = 3, initial_refinement_level = 0)

# A semidiscretization collects data structures and functions for the spatial discretization
semi = SemidiscretizationHyperbolic(mesh, equations, initial_condition, solver,
boundary_conditions = boundary_conditions)

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

# Create ODE problem with time span from 0.0 to 1.0
tspan = (0.0, 1.0)
ode = semidiscretize(semi, tspan)

# At the beginning of the main loop, the SummaryCallback prints a summary of the simulation setup
# and resets the timers
summary_callback = SummaryCallback()

# The AnalysisCallback allows to analyse the solution in regular intervals and prints the results
analysis_callback = AnalysisCallback(semi, interval = 100)

# The SaveSolutionCallback allows to save the solution to a file in regular intervals
save_solution = SaveSolutionCallback(interval = 100,
solution_variables = cons2prim)

# The StepsizeCallback handles the re-calculation of the maximum Δt after each time step
stepsize_callback = StepsizeCallback(cfl = 1.2)

# Create a CallbackSet to collect all callbacks such that they can be passed to the ODE solver
callbacks = CallbackSet(summary_callback, analysis_callback, save_solution,
stepsize_callback)

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

# OrdinaryDiffEq's `solve` method evolves the solution in time and executes the passed callbacks
sol = solve(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);

# Print the timer summary
summary_callback()
299 changes: 299 additions & 0 deletions examples/t8code_3d_dgsem/elixir_euler_baroclinic_instability.jl
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# An idealized baroclinic instability test case
# For optimal results consider increasing the resolution to 16x16x8 trees per cube face.
#
# Note that this elixir can take several hours to run.
# Using 24 threads of an AMD Ryzen Threadripper 3990X (more threads don't speed it up further)
# and `check-bounds=no`, this elixirs takes about one hour to run.
# With 16x16x8 trees per cube face on the same machine, it takes about 28 hours.
#
# References:
# - Paul A. Ullrich, Thomas Melvin, Christiane Jablonowski, Andrew Staniforth (2013)
# A proposed baroclinic wave test case for deep- and shallow-atmosphere dynamical cores
# https://doi.org/10.1002/qj.2241

using OrdinaryDiffEq
using Trixi
using LinearAlgebra

###############################################################################
# Setup for the baroclinic instability test
gamma = 1.4
equations = CompressibleEulerEquations3D(gamma)

# Initial condition for an idealized baroclinic instability test
# https://doi.org/10.1002/qj.2241, Section 3.2 and Appendix A
function initial_condition_baroclinic_instability(x, t,
equations::CompressibleEulerEquations3D)
lon, lat, r = cartesian_to_sphere(x)
radius_earth = 6.371229e6
# Make sure that the r is not smaller than radius_earth
z = max(r - radius_earth, 0.0)

# Unperturbed basic state
rho, u, p = basic_state_baroclinic_instability_longitudinal_velocity(lon, lat, z)

# Stream function type perturbation
u_perturbation, v_perturbation = perturbation_stream_function(lon, lat, z)

u += u_perturbation
v = v_perturbation

# Convert spherical velocity to Cartesian
v1 = -sin(lon) * u - sin(lat) * cos(lon) * v
v2 = cos(lon) * u - sin(lat) * sin(lon) * v
v3 = cos(lat) * v

return prim2cons(SVector(rho, v1, v2, v3, p), equations)
end

# Steady state for RHS correction below
function steady_state_baroclinic_instability(x, t, equations::CompressibleEulerEquations3D)
lon, lat, r = cartesian_to_sphere(x)
radius_earth = 6.371229e6
# Make sure that the r is not smaller than radius_earth
z = max(r - radius_earth, 0.0)

# Unperturbed basic state
rho, u, p = basic_state_baroclinic_instability_longitudinal_velocity(lon, lat, z)

# Convert spherical velocity to Cartesian
v1 = -sin(lon) * u
v2 = cos(lon) * u
v3 = 0.0

return prim2cons(SVector(rho, v1, v2, v3, p), equations)
end

function cartesian_to_sphere(x)
r = norm(x)
lambda = atan(x[2], x[1])
if lambda < 0
lambda += 2 * pi
end
phi = asin(x[3] / r)

return lambda, phi, r
end

# Unperturbed balanced steady-state.
# Returns primitive variables with only the velocity in longitudinal direction (rho, u, p).
# The other velocity components are zero.
function basic_state_baroclinic_instability_longitudinal_velocity(lon, lat, z)
# Parameters from Table 1 in the paper
# Corresponding names in the paper are commented
radius_earth = 6.371229e6 # a
half_width_parameter = 2 # b
gravitational_acceleration = 9.80616 # g
k = 3 # k
surface_pressure = 1e5 # p₀
gas_constant = 287 # R
surface_equatorial_temperature = 310.0 # T₀ᴱ
surface_polar_temperature = 240.0 # T₀ᴾ
lapse_rate = 0.005 # Γ
angular_velocity = 7.29212e-5 # Ω

# Distance to the center of the Earth
r = z + radius_earth

# In the paper: T₀
temperature0 = 0.5 * (surface_equatorial_temperature + surface_polar_temperature)
# In the paper: A, B, C, H
const_a = 1 / lapse_rate
const_b = (temperature0 - surface_polar_temperature) /
(temperature0 * surface_polar_temperature)
const_c = 0.5 * (k + 2) * (surface_equatorial_temperature - surface_polar_temperature) /
(surface_equatorial_temperature * surface_polar_temperature)
const_h = gas_constant * temperature0 / gravitational_acceleration

# In the paper: (r - a) / bH
scaled_z = z / (half_width_parameter * const_h)

# Temporary variables
temp1 = exp(lapse_rate / temperature0 * z)
temp2 = exp(-scaled_z^2)

# In the paper: ̃τ₁, ̃τ₂
tau1 = const_a * lapse_rate / temperature0 * temp1 +
const_b * (1 - 2 * scaled_z^2) * temp2
tau2 = const_c * (1 - 2 * scaled_z^2) * temp2

# In the paper: ∫τ₁(r') dr', ∫τ₂(r') dr'
inttau1 = const_a * (temp1 - 1) + const_b * z * temp2
inttau2 = const_c * z * temp2

# Temporary variables
temp3 = r / radius_earth * cos(lat)
temp4 = temp3^k - k / (k + 2) * temp3^(k + 2)

# In the paper: T
temperature = 1 / ((r / radius_earth)^2 * (tau1 - tau2 * temp4))

# In the paper: U, u (zonal wind, first component of spherical velocity)
big_u = gravitational_acceleration / radius_earth * k * temperature * inttau2 *
(temp3^(k - 1) - temp3^(k + 1))
temp5 = radius_earth * cos(lat)
u = -angular_velocity * temp5 + sqrt(angular_velocity^2 * temp5^2 + temp5 * big_u)

# Hydrostatic pressure
p = surface_pressure *
exp(-gravitational_acceleration / gas_constant * (inttau1 - inttau2 * temp4))

# Density (via ideal gas law)
rho = p / (gas_constant * temperature)

return rho, u, p
end

# Perturbation as in Equations 25 and 26 of the paper (analytical derivative)
function perturbation_stream_function(lon, lat, z)
# Parameters from Table 1 in the paper
# Corresponding names in the paper are commented
perturbation_radius = 1 / 6 # d₀ / a
perturbed_wind_amplitude = 1.0 # Vₚ
perturbation_lon = pi / 9 # Longitude of perturbation location
perturbation_lat = 2 * pi / 9 # Latitude of perturbation location
pertz = 15000 # Perturbation height cap

# Great circle distance (d in the paper) divided by a (radius of the Earth)
# because we never actually need d without dividing by a
great_circle_distance_by_a = acos(sin(perturbation_lat) * sin(lat) +
cos(perturbation_lat) * cos(lat) *
cos(lon - perturbation_lon))

# In the first case, the vertical taper function is per definition zero.
# In the second case, the stream function is per definition zero.
if z > pertz || great_circle_distance_by_a > perturbation_radius
return 0.0, 0.0
end

# Vertical tapering of stream function
perttaper = 1.0 - 3 * z^2 / pertz^2 + 2 * z^3 / pertz^3

# sin/cos(pi * d / (2 * d_0)) in the paper
sin_, cos_ = sincos(0.5 * pi * great_circle_distance_by_a / perturbation_radius)

# Common factor for both u and v
factor = 16 / (3 * sqrt(3)) * perturbed_wind_amplitude * perttaper * cos_^3 * sin_

u_perturbation = -factor * (-sin(perturbation_lat) * cos(lat) +
cos(perturbation_lat) * sin(lat) * cos(lon - perturbation_lon)) /
sin(great_circle_distance_by_a)

v_perturbation = factor * cos(perturbation_lat) * sin(lon - perturbation_lon) /
sin(great_circle_distance_by_a)

return u_perturbation, v_perturbation
end

@inline function source_terms_baroclinic_instability(u, x, t,
equations::CompressibleEulerEquations3D)
radius_earth = 6.371229e6 # a
gravitational_acceleration = 9.80616 # g
angular_velocity = 7.29212e-5 # Ω

r = norm(x)
# Make sure that r is not smaller than radius_earth
z = max(r - radius_earth, 0.0)
r = z + radius_earth

du1 = zero(eltype(u))

# Gravity term
temp = -gravitational_acceleration * radius_earth^2 / r^3
du2 = temp * u[1] * x[1]
du3 = temp * u[1] * x[2]
du4 = temp * u[1] * x[3]
du5 = temp * (u[2] * x[1] + u[3] * x[2] + u[4] * x[3])

# Coriolis term, -2Ω × ρv = -2 * angular_velocity * (0, 0, 1) × u[2:4]
du2 -= -2 * angular_velocity * u[3]
du3 -= 2 * angular_velocity * u[2]

return SVector(du1, du2, du3, du4, du5)
end

###############################################################################
# Start of the actual elixir, semidiscretization of the problem

initial_condition = initial_condition_baroclinic_instability

boundary_conditions = Dict(:inside => boundary_condition_slip_wall,
:outside => boundary_condition_slip_wall)

# 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)
volume_flux = flux_kennedy_gruber
solver = DGSEM(polydeg = 5, surface_flux = surface_flux,
volume_integral = VolumeIntegralFluxDifferencing(volume_flux))

# For optimal results, use (16, 8) here
trees_per_cube_face = (8, 4)
mesh = Trixi.T8codeMeshCubedSphere(trees_per_cube_face..., 6.371229e6, 30000.0,
polydeg = 5, initial_refinement_level = 0)

semi = SemidiscretizationHyperbolic(mesh, equations, initial_condition, solver,
source_terms = source_terms_baroclinic_instability,
boundary_conditions = boundary_conditions)

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

tspan = (0.0, 10 * 24 * 60 * 60.0) # time in seconds for 10 days

# Save RHS of the steady state and subtract it in every RHS evaluation.
# This trick preserves the steady state exactly (to machine rounding errors, of course).
# Otherwise, this elixir produces entirely unusable results for a resolution of 8x8x4 cells
# per cube face with a polydeg of 3.
# With this trick, even the polydeg 3 simulation produces usable (although badly resolved) results,
# and most of the grid imprinting in higher polydeg simulation is eliminated.
#
# See https://github.com/trixi-framework/Trixi.jl/issues/980 for more information.
u_steady_state = compute_coefficients(steady_state_baroclinic_instability, tspan[1], semi)
# Use a `let` block for performance (otherwise du_steady_state will be a global variable)
let du_steady_state = similar(u_steady_state)
# Save RHS of the steady state
Trixi.rhs!(du_steady_state, u_steady_state, semi, tspan[1])

global function corrected_rhs!(du, u, semi, t)
# Normal RHS evaluation
Trixi.rhs!(du, u, semi, t)
# Correct by subtracting the steady-state RHS
Trixi.@trixi_timeit Trixi.timer() "rhs correction" begin
# Use Trixi.@threaded for threaded performance
Trixi.@threaded for i in eachindex(du)
du[i] -= du_steady_state[i]
end
end
end
end
u0 = compute_coefficients(tspan[1], semi)
ode = ODEProblem(corrected_rhs!, u0, tspan, semi)

summary_callback = SummaryCallback()

analysis_interval = 5000
analysis_callback = AnalysisCallback(semi, interval = analysis_interval)

alive_callback = AliveCallback(analysis_interval = analysis_interval)

save_solution = SaveSolutionCallback(interval = 5000,
save_initial_solution = true,
save_final_solution = true,
solution_variables = cons2prim)

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

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

# Use a Runge-Kutta method with automatic (error based) time step size control
# Enable threading of the RK method for better performance on multiple threads
sol = solve(ode, RDPK3SpFSAL49(thread = OrdinaryDiffEq.True()); abstol = 1.0e-6,
reltol = 1.0e-6,
ode_default_options()..., callback = callbacks);

summary_callback() # print the timer summary
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