Taylor green vortex in SPH#

This simple example shows a SPH simulation of a Taylor green vortex

t = 0.000 [code unit]
Mach number : 0.10000000000000002
----- SPH Solver configuration -----
units :
not set
part mass 0 ( can be changed using .set_part_mass() )
cfl force 0.1
cfl courant 0.1
--- artificial viscosity config
  Config Type : VaryingCD10 (Cullen & Dehnen 2010)
  alpha_min   = 0
  alpha_max   = 1
  sigma_decay = 0.1
  alpha_u     = 1
  beta_AV     = 2
--- artificial viscosity config (deduced)
-------------
EOS config f64_3 :
adiabatic :
gamma 1.4
--- Bondaries config
  Config Type : Periodic boundaries
--- Bondaries config config (deduced)
-------------
------------------------------------
Box size :  256.0 221.70250336881628 209.02312471749784
Info: pushing data in scheduler, N = 132224                           [DataInserterUtility][rank=0]
Info: reattributing data ...                                          [DataInserterUtility][rank=0]
Info: reattributing data done in  23.55 ms                            [DataInserterUtility][rank=0]
Info: run scheduler step ...                                          [DataInserterUtility][rank=0]
Info: Scheduler step timings :                                                  [Scheduler][rank=0]
   metadata sync     : 3.61 us    (39.0%)
Info: summary :                                                               [LoadBalance][rank=0]
Info:  - strategy "psweep" : max = 132224 min = 132224                        [LoadBalance][rank=0]
Info:  - strategy "round robin" : max = 132224 min = 132224                   [LoadBalance][rank=0]
Info: Loadbalance stats :                                                     [LoadBalance][rank=0]
    npatch = 1
    min = 132224
    max = 132224
    avg = 132224
    efficiency = 100.00%
Info: Scheduler step timings :                                                  [Scheduler][rank=0]
   metadata sync     : 1052.00 ns (0.2%)
   patch tree reduce : 1052.00 ns (0.2%)
   gen split merge   : 1052.00 ns (0.2%)
   split / merge op  : 0/0
   apply split merge : 912.00 ns  (0.2%)
   LB compute        : 446.74 us  (97.9%)
   LB move op cnt    : 0
   LB apply          : 1883.00 ns (0.4%)
Info: the setup took : 0.07165858400000001 s                                    [SPH setup][rank=0]
Total mass : 0.046875
Current part mass : 3.5451204017424977e-07
---------------- t = 0, dt = 0 ----------------
Info: summary :                                                               [LoadBalance][rank=0]
Info:  - strategy "psweep" : max = 132224 min = 132224                        [LoadBalance][rank=0]
Info:  - strategy "round robin" : max = 132224 min = 132224                   [LoadBalance][rank=0]
Info: Loadbalance stats :                                                     [LoadBalance][rank=0]
    npatch = 1
    min = 132224
    max = 132224
    avg = 132224
    efficiency = 100.00%
Info: Scheduler step timings :                                                  [Scheduler][rank=0]
   metadata sync     : 7.38 us    (1.3%)
   patch tree reduce : 1403.00 ns (0.2%)
   gen split merge   : 1032.00 ns (0.2%)
   split / merge op  : 0/0
   apply split merge : 1433.00 ns (0.3%)
   LB compute        : 548.78 us  (96.4%)
   LB move op cnt    : 0
   LB apply          : 1974.00 ns (0.3%)
Info: Scheduler step timings :                                                  [Scheduler][rank=0]
   metadata sync     : 2.06 us    (68.7%)
Warning: High interface/patch volume ratio.                                  [InterfaceGen][rank=0]
    This can lead to high mpi overhead, try to increase the patch split crit
    patch 0 high interf/patch volume: 0.6578911544046468
Warning: smoothing length is not converged, rerunning the iterator ...    [Smoothinglength][rank=0]
     largest h = 0.004296875 unconverged cnt = 132224
Warning: High interface/patch volume ratio.                                  [InterfaceGen][rank=0]
    This can lead to high mpi overhead, try to increase the patch split crit
    patch 0 high interf/patch volume: 0.6578911544046468
Warning: smoothing length is not converged, rerunning the iterator ...    [Smoothinglength][rank=0]
     largest h = 0.004726562500000001 unconverged cnt = 132224
Warning: High interface/patch volume ratio.                                  [InterfaceGen][rank=0]
    This can lead to high mpi overhead, try to increase the patch split crit
    patch 0 high interf/patch volume: 0.6638809898354309
Warning: smoothing length is not converged, rerunning the iterator ...    [Smoothinglength][rank=0]
     largest h = 0.005199218750000002 unconverged cnt = 132224
Warning: High interface/patch volume ratio.                                  [InterfaceGen][rank=0]
    This can lead to high mpi overhead, try to increase the patch split crit
    patch 0 high interf/patch volume: 0.9830817400774442
Warning: smoothing length is not converged, rerunning the iterator ...    [Smoothinglength][rank=0]
     largest h = 0.0057191406250000024 unconverged cnt = 132224
Warning: High interface/patch volume ratio.                                  [InterfaceGen][rank=0]
    This can lead to high mpi overhead, try to increase the patch split crit
    patch 0 high interf/patch volume: 0.9911286907066795
Warning: smoothing length is not converged, rerunning the iterator ...    [Smoothinglength][rank=0]
     largest h = 0.006291054687500003 unconverged cnt = 132224
Warning: High interface/patch volume ratio.                                  [InterfaceGen][rank=0]
    This can lead to high mpi overhead, try to increase the patch split crit
    patch 0 high interf/patch volume: 1.0163283518877058
Warning: smoothing length is not converged, rerunning the iterator ...    [Smoothinglength][rank=0]
     largest h = 0.006920160156250004 unconverged cnt = 132224
Warning: High interface/patch volume ratio.                                  [InterfaceGen][rank=0]
    This can lead to high mpi overhead, try to increase the patch split crit
    patch 0 high interf/patch volume: 1.0243753025169406
Info: smoothing length iteration converged                                [Smoothinglength][rank=0]
  eps min = 1.9302601001271766e-10, max = 9.282277784123224e-07
  iterations = 3
Info: conservation infos :                                                     [sph::Model][rank=0]
    sum v = (-6.045502917247344e-20,1.763271684197142e-20,0)
    sum a = (1.0513199723902636e-15,-6.716150707533982e-16,-1.2009754275286882e-14)
    sum e = 8.382254464285712
    sum de = 7.605678239985814e-17
Info: cfl dt = 6.796398329179769e-07 cfl multiplier : 0.01                     [sph::Model][rank=0]
Info: processing rate infos :                                                  [sph::Model][rank=0]
---------------------------------------------------------------------------------------
| rank |  rate  (N.s^-1)  |     Nobj    | t compute (s) | interf | alloc |  mem (max) |
---------------------------------------------------------------------------------------
| 0    |    3.5718e+04    |      132224 |   3.702e+00   |   14 % |   0 % |  160.18 MB |
---------------------------------------------------------------------------------------
Info: estimated rate : 0 (tsim/hr)                                             [sph::Model][rank=0]
Info: iteration since start : 1                                                       [SPH][rank=0]
Info: time since start : 14.692532593000001 (s)                                       [SPH][rank=0]
Info: dump to _to_trash/dump_0000.vtk                                            [VTK Dump][rank=0]
              - took 15.20 ms, bandwidth = 696.95 MB/s
Info: compute_slice field_name: vxyz, center: (0,0,0), delta_x: (1,0,0), delta_y: (0,1,0), nx: 1080, ny: 1080  [sph::CartesianRender][rank=0]
Info: compute_slice took 2.33 s                                      [sph::CartesianRender][rank=0]

  8 import matplotlib.pyplot as plt
  9 import numpy as np
 10
 11 import shamrock
 12
 13 # If we use the shamrock executable to run this script instead of the python interpreter,
 14 # we should not initialize the system as the shamrock executable needs to handle specific MPI logic
 15 if not shamrock.sys.is_initialized():
 16     shamrock.change_loglevel(1)
 17     shamrock.sys.init("0:0")
 18
 19 gamma = 1.4
 20
 21 rho_g = 1
 22
 23 Mach = 0.1
 24 P_g = (Mach**-2) * rho_g / gamma
 25
 26 print(f"Mach number : {1/np.sqrt(gamma*P_g/rho_g)}")
 27
 28 u_g = P_g / ((gamma - 1) * rho_g)
 29
 30 resol_per_green = 128
 31 vortex_size = 1
 32
 33 L_green = vortex_size / (2 * np.pi)
 34
 35 ctx = shamrock.Context()
 36 ctx.pdata_layout_new()
 37
 38 model = shamrock.get_Model_SPH(context=ctx, vector_type="f64_3", sph_kernel="M6")
 39
 40 cfg = model.gen_default_config()
 41 cfg.set_artif_viscosity_VaryingCD10(
 42     alpha_min=0.0, alpha_max=1, sigma_decay=0.1, alpha_u=1, beta_AV=2
 43 )
 44 cfg.set_boundary_periodic()
 45 cfg.set_eos_adiabatic(gamma)
 46 # Set the CFL
 47 cfg.set_cfl_cour(0.1)
 48 cfg.set_cfl_force(0.1)
 49
 50 # Set the solver config to be the one stored in cfg
 51 model.set_solver_config(cfg)
 52
 53 # Print the solver config
 54 model.get_current_config().print_status()
 55
 56 # We want the patches to split above 10^8 part and merge if smaller than 1 part (e.g. disable patch)
 57 model.init_scheduler(int(1e8), 1)
 58
 59
 60 resol = resol_per_green
 61 (xs, ys, zs) = model.get_box_dim_fcc_3d(1, resol, resol, resol)
 62 dr = 1 / xs
 63
 64 print("Box size : ", xs, ys, zs)
 65 (xs, ys, zs) = (1.0, 1.0, dr * 12)
 66
 67 model.resize_simulation_box((-xs / 2, -ys / 2, -zs / 2), (xs / 2, ys / 2, zs / 2))
 68
 69
 70 setup = model.get_setup()
 71 gen1 = setup.make_generator_lattice_hcp(dr, (-xs / 2, -ys / 2, -zs / 2), (xs / 2, ys / 2, zs / 2))
 72 setup.apply_setup(gen1)
 73
 74 model.set_value_in_a_box("uint", "f64", u_g, (-xs / 2, -ys / 2, -zs / 2), (xs / 2, ys / 2, zs / 2))
 75
 76
 77 def vel_func(r):
 78     x, y, z = r
 79
 80     x += L_green * np.pi
 81
 82     vx = np.cos(x / L_green) * np.sin(y / L_green)
 83     vy = -np.sin(x / L_green) * np.cos(y / L_green)
 84     vz = 0
 85
 86     return (vx, vy, vz)
 87
 88
 89 model.set_field_value_lambda_f64_3("vxyz", vel_func)
 90
 91
 92 vol_b = xs * ys * zs
 93
 94 totmass = rho_g * vol_b
 95
 96 print("Total mass :", totmass)
 97
 98
 99 pmass = model.total_mass_to_part_mass(totmass)
100 model.set_particle_mass(pmass)
101 print("Current part mass :", pmass)
102
103
104 dump_folder = "_to_trash"
105 import os
106
107 os.system("mkdir -p " + dump_folder)
108
109 current_fig = None
110
111 cnt_plot = 0
112
113
114 def plot():
115     global current_fig
116     if current_fig is not None:
117         plt.close(current_fig)
118
119     pixel_x = 1080
120     pixel_y = 1080
121     radius = 0.5
122     center = (0.0, 0.0, 0.0)
123     aspect = pixel_x / pixel_y
124     pic_range = [-radius * aspect, radius * aspect, -radius, radius]
125     delta_x = (radius * 2 * aspect, 0.0, 0.0)
126     delta_y = (0.0, radius * 2, 0.0)
127
128     arr_vel = model.render_cartesian_slice(
129         "vxyz",
130         "f64_3",
131         center=(0.0, 0.0, 0.0),
132         delta_x=delta_x,
133         delta_y=delta_y,
134         nx=pixel_x,
135         ny=pixel_y,
136     )
137
138     v_norm = np.sqrt(arr_vel[:, :, 0] ** 2 + arr_vel[:, :, 1] ** 2 + arr_vel[:, :, 2] ** 2)
139
140     import copy
141
142     import matplotlib
143
144     my_cmap = copy.copy(matplotlib.colormaps.get_cmap("gist_heat"))  # copy the default cmap
145     my_cmap.set_bad(color="black")
146
147     fig_width = 6
148     fig_height = fig_width / aspect
149     current_fig = plt.figure(figsize=(fig_width, fig_height))
150     res = plt.imshow(v_norm, cmap=my_cmap, origin="lower", extent=pic_range)
151
152     cbar = plt.colorbar(res, extend="both")
153     cbar.set_label(r"$\sqrt{vx^2 + vy^2 + vz^2}$ [code unit]")
154
155     plt.title("t = {:0.3f} [code unit]".format(model.get_time()))
156     plt.xlabel("x")
157     plt.ylabel("y")
158     global cnt_plot
159     plt.savefig(dump_folder + f"/test_{cnt_plot}.png")
160     cnt_plot += 1
161
162
163 model.timestep()
164
165 dt_stop = 0.001
166 for i in range(1):
167
168     t_target = i * dt_stop
169     # skip if the model is already past the target
170     if model.get_time() > t_target:
171         continue
172
173     model.evolve_until(i * dt_stop)
174
175     # Dump name is "dump_xxxx.sham" where xxxx is the timestep
176     model.do_vtk_dump(dump_folder + "/dump_{:04}.vtk".format(i), True)
177     plot()

Total running time of the script: (0 minutes 7.081 seconds)

Estimated memory usage: 253 MB

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