elixir_advection_meshview.jl

using OrdinaryDiffEqLowStorageRK
using Trixi

###############################################################################
# Most basic p4est mesh view setup where the entire domain
# is part of the single mesh view.

advection_velocity = (0.2, -0.7)
equations = LinearScalarAdvectionEquation2D(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)

coordinates_min = (-1.0, -1.0) # minimum coordinates (min(x), min(y))
coordinates_max = (1.0, 1.0) # maximum coordinates (max(x), max(y))

trees_per_dimension = (8, 8)

# Create parent P4estMesh with 8 x 8 trees and 8 x 8 elements
parent_mesh = P4estMesh(trees_per_dimension, polydeg = 3,
                        coordinates_min = coordinates_min,
                        coordinates_max = coordinates_max,
                        initial_refinement_level = 0)

# Define the mesh view covering the whole parent mesh.
cell_ids = collect(1:Trixi.ncells(parent_mesh))
mesh = P4estMeshView(parent_mesh, cell_ids)

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

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

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

# 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
# We require this definition for the test, even though we don't use it in the CallbackSet.
analysis_callback = AnalysisCallback(semi)

# 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 = 1.6)

# Create a CallbackSet to collect all callbacks such that they can be passed to the ODE solver
callbacks = CallbackSet(summary_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
            ode_default_options()..., callback = callbacks);