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- name: Checkout Actions Repository | ||
uses: actions/checkout@v3 | ||
- name: Check spelling | ||
uses: crate-ci/[email protected].1 | ||
uses: crate-ci/[email protected].10 |
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name = "Trixi" | ||
uuid = "a7f1ee26-1774-49b1-8366-f1abc58fbfcb" | ||
authors = ["Michael Schlottke-Lakemper <[email protected]>", "Gregor Gassner <[email protected]>", "Hendrik Ranocha <[email protected]>", "Andrew R. Winters <[email protected]>", "Jesse Chan <[email protected]>"] | ||
version = "0.5.30-pre" | ||
version = "0.5.31-pre" | ||
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[deps] | ||
CodeTracking = "da1fd8a2-8d9e-5ec2-8556-3022fb5608a2" | ||
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examples/p4est_2d_dgsem/elixir_advection_diffusion_nonperiodic_curved.jl
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using OrdinaryDiffEq | ||
using Trixi | ||
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############################################################################### | ||
# semidiscretization of the linear advection-diffusion equation | ||
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diffusivity() = 5.0e-2 | ||
advection_velocity = (1.0, 0.0) | ||
equations = LinearScalarAdvectionEquation2D(advection_velocity) | ||
equations_parabolic = LaplaceDiffusion2D(diffusivity(), equations) | ||
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# Example setup taken from | ||
# - Truman Ellis, Jesse Chan, and Leszek Demkowicz (2016). | ||
# Robust DPG methods for transient convection-diffusion. | ||
# In: Building bridges: connections and challenges in modern approaches | ||
# to numerical partial differential equations. | ||
# [DOI](https://doi.org/10.1007/978-3-319-41640-3_6). | ||
function initial_condition_eriksson_johnson(x, t, equations) | ||
l = 4 | ||
epsilon = diffusivity() # TODO: this requires epsilon < .6 due to sqrt | ||
lambda_1 = (-1 + sqrt(1 - 4 * epsilon * l)) / (-2 * epsilon) | ||
lambda_2 = (-1 - sqrt(1 - 4 * epsilon * l)) / (-2 * epsilon) | ||
r1 = (1 + sqrt(1 + 4 * pi^2 * epsilon^2)) / (2 * epsilon) | ||
s1 = (1 - sqrt(1 + 4 * pi^2 * epsilon^2)) / (2 * epsilon) | ||
u = exp(-l * t) * (exp(lambda_1 * x[1]) - exp(lambda_2 * x[1])) + | ||
cos(pi * x[2]) * (exp(s1 * x[1]) - exp(r1 * x[1])) / (exp(-s1) - exp(-r1)) | ||
return SVector{1}(u) | ||
end | ||
initial_condition = initial_condition_eriksson_johnson | ||
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boundary_conditions = Dict(:x_neg => BoundaryConditionDirichlet(initial_condition), | ||
:y_neg => BoundaryConditionDirichlet(initial_condition), | ||
:y_pos => BoundaryConditionDirichlet(initial_condition), | ||
:x_pos => boundary_condition_do_nothing) | ||
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boundary_conditions_parabolic = Dict(:x_neg => BoundaryConditionDirichlet(initial_condition), | ||
:x_pos => BoundaryConditionDirichlet(initial_condition), | ||
:y_neg => BoundaryConditionDirichlet(initial_condition), | ||
:y_pos => BoundaryConditionDirichlet(initial_condition)) | ||
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# 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) | ||
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coordinates_min = (-1.0, -0.5) | ||
coordinates_max = ( 0.0, 0.5) | ||
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# This maps the domain [-1, 1]^2 to [-1, 0] x [-0.5, 0.5] while also | ||
# introducing a curved warping to interior nodes. | ||
function mapping(xi, eta) | ||
x = xi + 0.1 * sin(pi * xi) * sin(pi * eta) | ||
y = eta + 0.1 * sin(pi * xi) * sin(pi * eta) | ||
return SVector(0.5 * (1 + x) - 1, 0.5 * y) | ||
end | ||
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trees_per_dimension = (4, 4) | ||
mesh = P4estMesh(trees_per_dimension, | ||
polydeg=3, initial_refinement_level=2, | ||
mapping=mapping, periodicity=(false, false)) | ||
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# A semidiscretization collects data structures and functions for the spatial discretization | ||
semi = SemidiscretizationHyperbolicParabolic(mesh, (equations, equations_parabolic), initial_condition, solver, | ||
boundary_conditions = (boundary_conditions, boundary_conditions_parabolic)) | ||
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############################################################################### | ||
# ODE solvers, callbacks etc. | ||
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# Create ODE problem with time span `tspan` | ||
tspan = (0.0, 1.0) | ||
ode = semidiscretize(semi, tspan); | ||
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# At the beginning of the main loop, the SummaryCallback prints a summary of the simulation setup | ||
# and resets the timers | ||
summary_callback = SummaryCallback() | ||
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# The AnalysisCallback allows to analyse the solution in regular intervals and prints the results | ||
analysis_interval = 100 | ||
analysis_callback = AnalysisCallback(semi, interval=analysis_interval) | ||
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# The AliveCallback prints short status information in regular intervals | ||
alive_callback = AliveCallback(analysis_interval=analysis_interval) | ||
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# Create a CallbackSet to collect all callbacks such that they can be passed to the ODE solver | ||
callbacks = CallbackSet(summary_callback, analysis_callback, alive_callback) | ||
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############################################################################### | ||
# run the simulation | ||
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# OrdinaryDiffEq's `solve` method evolves the solution in time and executes the passed callbacks | ||
time_int_tol = 1.0e-11 | ||
sol = solve(ode, RDPK3SpFSAL49(); abstol=time_int_tol, reltol=time_int_tol, | ||
ode_default_options()..., callback=callbacks) | ||
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# Print the timer summary | ||
summary_callback() |
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examples/p4est_2d_dgsem/elixir_navierstokes_convergence.jl
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using OrdinaryDiffEq | ||
using Trixi | ||
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############################################################################### | ||
# semidiscretization of the ideal compressible Navier-Stokes equations | ||
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prandtl_number() = 0.72 | ||
mu() = 0.01 | ||
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equations = CompressibleEulerEquations2D(1.4) | ||
equations_parabolic = CompressibleNavierStokesDiffusion2D(equations, mu=mu(), Prandtl=prandtl_number(), | ||
gradient_variables=GradientVariablesPrimitive()) | ||
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# 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, | ||
volume_integral=VolumeIntegralWeakForm()) | ||
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coordinates_min = (-1.0, -1.0) # minimum coordinates (min(x), min(y)) | ||
coordinates_max = ( 1.0, 1.0) # maximum coordinates (max(x), max(y)) | ||
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trees_per_dimension = (4, 4) | ||
mesh = P4estMesh(trees_per_dimension, | ||
polydeg=3, initial_refinement_level=2, | ||
coordinates_min=coordinates_min, coordinates_max=coordinates_max, | ||
periodicity=(true, false)) | ||
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# Note: the initial condition cannot be specialized to `CompressibleNavierStokesDiffusion2D` | ||
# since it is called by both the parabolic solver (which passes in `CompressibleNavierStokesDiffusion2D`) | ||
# and by the initial condition (which passes in `CompressibleEulerEquations2D`). | ||
# This convergence test setup was originally derived by Andrew Winters (@andrewwinters5000) | ||
function initial_condition_navier_stokes_convergence_test(x, t, equations) | ||
# Amplitude and shift | ||
A = 0.5 | ||
c = 2.0 | ||
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# convenience values for trig. functions | ||
pi_x = pi * x[1] | ||
pi_y = pi * x[2] | ||
pi_t = pi * t | ||
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rho = c + A * sin(pi_x) * cos(pi_y) * cos(pi_t) | ||
v1 = sin(pi_x) * log(x[2] + 2.0) * (1.0 - exp(-A * (x[2] - 1.0)) ) * cos(pi_t) | ||
v2 = v1 | ||
p = rho^2 | ||
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return prim2cons(SVector(rho, v1, v2, p), equations) | ||
end | ||
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@inline function source_terms_navier_stokes_convergence_test(u, x, t, equations) | ||
y = x[2] | ||
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# TODO: parabolic | ||
# we currently need to hardcode these parameters until we fix the "combined equation" issue | ||
# see also https://github.com/trixi-framework/Trixi.jl/pull/1160 | ||
inv_gamma_minus_one = inv(equations.gamma - 1) | ||
Pr = prandtl_number() | ||
mu_ = mu() | ||
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# Same settings as in `initial_condition` | ||
# Amplitude and shift | ||
A = 0.5 | ||
c = 2.0 | ||
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# convenience values for trig. functions | ||
pi_x = pi * x[1] | ||
pi_y = pi * x[2] | ||
pi_t = pi * t | ||
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# compute the manufactured solution and all necessary derivatives | ||
rho = c + A * sin(pi_x) * cos(pi_y) * cos(pi_t) | ||
rho_t = -pi * A * sin(pi_x) * cos(pi_y) * sin(pi_t) | ||
rho_x = pi * A * cos(pi_x) * cos(pi_y) * cos(pi_t) | ||
rho_y = -pi * A * sin(pi_x) * sin(pi_y) * cos(pi_t) | ||
rho_xx = -pi * pi * A * sin(pi_x) * cos(pi_y) * cos(pi_t) | ||
rho_yy = -pi * pi * A * sin(pi_x) * cos(pi_y) * cos(pi_t) | ||
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v1 = sin(pi_x) * log(y + 2.0) * (1.0 - exp(-A * (y - 1.0))) * cos(pi_t) | ||
v1_t = -pi * sin(pi_x) * log(y + 2.0) * (1.0 - exp(-A * (y - 1.0))) * sin(pi_t) | ||
v1_x = pi * cos(pi_x) * log(y + 2.0) * (1.0 - exp(-A * (y - 1.0))) * cos(pi_t) | ||
v1_y = sin(pi_x) * (A * log(y + 2.0) * exp(-A * (y - 1.0)) + (1.0 - exp(-A * (y - 1.0))) / (y + 2.0)) * cos(pi_t) | ||
v1_xx = -pi * pi * sin(pi_x) * log(y + 2.0) * (1.0 - exp(-A * (y - 1.0))) * cos(pi_t) | ||
v1_xy = pi * cos(pi_x) * (A * log(y + 2.0) * exp(-A * (y - 1.0)) + (1.0 - exp(-A * (y - 1.0))) / (y + 2.0)) * cos(pi_t) | ||
v1_yy = (sin(pi_x) * ( 2.0 * A * exp(-A * (y - 1.0)) / (y + 2.0) | ||
- A * A * log(y + 2.0) * exp(-A * (y - 1.0)) | ||
- (1.0 - exp(-A * (y - 1.0))) / ((y + 2.0) * (y + 2.0))) * cos(pi_t)) | ||
v2 = v1 | ||
v2_t = v1_t | ||
v2_x = v1_x | ||
v2_y = v1_y | ||
v2_xx = v1_xx | ||
v2_xy = v1_xy | ||
v2_yy = v1_yy | ||
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p = rho * rho | ||
p_t = 2.0 * rho * rho_t | ||
p_x = 2.0 * rho * rho_x | ||
p_y = 2.0 * rho * rho_y | ||
p_xx = 2.0 * rho * rho_xx + 2.0 * rho_x * rho_x | ||
p_yy = 2.0 * rho * rho_yy + 2.0 * rho_y * rho_y | ||
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# Note this simplifies slightly because the ansatz assumes that v1 = v2 | ||
E = p * inv_gamma_minus_one + 0.5 * rho * (v1^2 + v2^2) | ||
E_t = p_t * inv_gamma_minus_one + rho_t * v1^2 + 2.0 * rho * v1 * v1_t | ||
E_x = p_x * inv_gamma_minus_one + rho_x * v1^2 + 2.0 * rho * v1 * v1_x | ||
E_y = p_y * inv_gamma_minus_one + rho_y * v1^2 + 2.0 * rho * v1 * v1_y | ||
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# Some convenience constants | ||
T_const = equations.gamma * inv_gamma_minus_one / Pr | ||
inv_rho_cubed = 1.0 / (rho^3) | ||
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# compute the source terms | ||
# density equation | ||
du1 = rho_t + rho_x * v1 + rho * v1_x + rho_y * v2 + rho * v2_y | ||
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# x-momentum equation | ||
du2 = ( rho_t * v1 + rho * v1_t + p_x + rho_x * v1^2 | ||
+ 2.0 * rho * v1 * v1_x | ||
+ rho_y * v1 * v2 | ||
+ rho * v1_y * v2 | ||
+ rho * v1 * v2_y | ||
# stress tensor from x-direction | ||
- 4.0 / 3.0 * v1_xx * mu_ | ||
+ 2.0 / 3.0 * v2_xy * mu_ | ||
- v1_yy * mu_ | ||
- v2_xy * mu_ ) | ||
# y-momentum equation | ||
du3 = ( rho_t * v2 + rho * v2_t + p_y + rho_x * v1 * v2 | ||
+ rho * v1_x * v2 | ||
+ rho * v1 * v2_x | ||
+ rho_y * v2^2 | ||
+ 2.0 * rho * v2 * v2_y | ||
# stress tensor from y-direction | ||
- v1_xy * mu_ | ||
- v2_xx * mu_ | ||
- 4.0 / 3.0 * v2_yy * mu_ | ||
+ 2.0 / 3.0 * v1_xy * mu_ ) | ||
# total energy equation | ||
du4 = ( E_t + v1_x * (E + p) + v1 * (E_x + p_x) | ||
+ v2_y * (E + p) + v2 * (E_y + p_y) | ||
# stress tensor and temperature gradient terms from x-direction | ||
- 4.0 / 3.0 * v1_xx * v1 * mu_ | ||
+ 2.0 / 3.0 * v2_xy * v1 * mu_ | ||
- 4.0 / 3.0 * v1_x * v1_x * mu_ | ||
+ 2.0 / 3.0 * v2_y * v1_x * mu_ | ||
- v1_xy * v2 * mu_ | ||
- v2_xx * v2 * mu_ | ||
- v1_y * v2_x * mu_ | ||
- v2_x * v2_x * mu_ | ||
- T_const * inv_rho_cubed * ( p_xx * rho * rho | ||
- 2.0 * p_x * rho * rho_x | ||
+ 2.0 * p * rho_x * rho_x | ||
- p * rho * rho_xx ) * mu_ | ||
# stress tensor and temperature gradient terms from y-direction | ||
- v1_yy * v1 * mu_ | ||
- v2_xy * v1 * mu_ | ||
- v1_y * v1_y * mu_ | ||
- v2_x * v1_y * mu_ | ||
- 4.0 / 3.0 * v2_yy * v2 * mu_ | ||
+ 2.0 / 3.0 * v1_xy * v2 * mu_ | ||
- 4.0 / 3.0 * v2_y * v2_y * mu_ | ||
+ 2.0 / 3.0 * v1_x * v2_y * mu_ | ||
- T_const * inv_rho_cubed * ( p_yy * rho * rho | ||
- 2.0 * p_y * rho * rho_y | ||
+ 2.0 * p * rho_y * rho_y | ||
- p * rho * rho_yy ) * mu_ ) | ||
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return SVector(du1, du2, du3, du4) | ||
end | ||
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initial_condition = initial_condition_navier_stokes_convergence_test | ||
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# BC types | ||
velocity_bc_top_bottom = NoSlip((x, t, equations) -> initial_condition_navier_stokes_convergence_test(x, t, equations)[2:3]) | ||
heat_bc_top_bottom = Adiabatic((x, t, equations) -> 0.0) | ||
boundary_condition_top_bottom = BoundaryConditionNavierStokesWall(velocity_bc_top_bottom, heat_bc_top_bottom) | ||
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# define inviscid boundary conditions | ||
boundary_conditions = Dict(:y_neg => boundary_condition_slip_wall, | ||
:y_pos => boundary_condition_slip_wall) | ||
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# define viscous boundary conditions | ||
boundary_conditions_parabolic = Dict(:y_neg => boundary_condition_top_bottom, | ||
:y_pos => boundary_condition_top_bottom) | ||
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semi = SemidiscretizationHyperbolicParabolic(mesh, (equations, equations_parabolic), initial_condition, solver; | ||
boundary_conditions=(boundary_conditions, boundary_conditions_parabolic), | ||
source_terms=source_terms_navier_stokes_convergence_test) | ||
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# ############################################################################### | ||
# # ODE solvers, callbacks etc. | ||
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# Create ODE problem with time span `tspan` | ||
tspan = (0.0, 0.5) | ||
ode = semidiscretize(semi, tspan) | ||
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summary_callback = SummaryCallback() | ||
alive_callback = AliveCallback(alive_interval=10) | ||
analysis_interval = 100 | ||
analysis_callback = AnalysisCallback(semi, interval=analysis_interval) | ||
callbacks = CallbackSet(summary_callback, alive_callback, analysis_callback) | ||
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############################################################################### | ||
# run the simulation | ||
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time_int_tol = 1e-8 | ||
sol = solve(ode, RDPK3SpFSAL49(); abstol=time_int_tol, reltol=time_int_tol, dt = 1e-5, | ||
ode_default_options()..., callback=callbacks) | ||
summary_callback() # print the timer summary | ||
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