diff options
Diffstat (limited to 'Examples/Modules/embedded_boundary_cube')
| -rw-r--r-- | Examples/Modules/embedded_boundary_cube/analysis_fields.py | 86 | ||||
| -rw-r--r-- | Examples/Modules/embedded_boundary_cube/inputs_3d | 37 |
2 files changed, 123 insertions, 0 deletions
diff --git a/Examples/Modules/embedded_boundary_cube/analysis_fields.py b/Examples/Modules/embedded_boundary_cube/analysis_fields.py new file mode 100644 index 000000000..58dad1bb7 --- /dev/null +++ b/Examples/Modules/embedded_boundary_cube/analysis_fields.py @@ -0,0 +1,86 @@ +#! /usr/bin/env python + +import yt +import os, sys +from scipy.constants import mu_0, pi, c +import numpy as np +sys.path.insert(1, '../../../../warpx/Regression/Checksum/') +import checksumAPI + +# This is a script that analyses the simulation results from +# the script `inputs_3d`. This simulates a TMmnp mode in a PEC cubic resonator. +# The magnetic field in the simulation is given (in theory) by: +# $$ B_x = \frac{-2\mu}{h^2}\, k_x k_z \sin(k_x x)\cos(k_y y)\cos(k_z z)\cos( \omega_p t)$$ +# $$ B_y = \frac{-2\mu}{h^2}\, k_y k_z \cos(k_x x)\sin(k_y y)\cos(k_z z)\cos( \omega_p t)$$ +# $$ B_z = \cos(k_x x)\cos(k_y y)\sin(k_z z)\sin( \omega_p t)$$ +# with +# $$ h^2 = k_x^2 + k_y^2 + k_z^2$$ +# $$ k_x = \frac{m\pi}{L}$$ +# $$ k_y = \frac{n\pi}{L}$$ +# $$ k_z = \frac{p\pi}{L}$$ + +hi = [0.8, 0.8, 0.8] +lo = [-0.8, -0.8, -0.8] +ncells = [48, 48, 48] +dx = (hi[0] - lo[0])/ncells[0] +dy = (hi[1] - lo[1])/ncells[1] +dz = (hi[2] - lo[2])/ncells[2] +m = 0 +n = 1 +p = 1 +Lx = 1 +Ly = 1 +Lz = 1 +h_2 = (m * pi / Lx) ** 2 + (n * pi / Ly) ** 2 + (p * pi / Lz) ** 2 +t = 1.3342563807926085e-08 + +# Compute the analytic solution +Bx_th = np.zeros(ncells) +By_th = np.zeros(ncells) +Bz_th = np.zeros(ncells) +for i in range(ncells[0]): + for j in range(ncells[1]): + for k in range(ncells[2]): + x = i*dx + lo[0] + y = (j+0.5)*dy + lo[1] + z = k*dz + lo[2] + + By_th[i, j, k] = -2/h_2*mu_0*(n * pi/Ly)*(p * pi/Lz) * (np.cos(m * pi/Lx * (x - Lx/2)) * + np.sin(n * pi/Ly * (y - Ly/2)) * + np.cos(p * pi/Lz * (z - Lz/2)) * + (-Lx/2 <= x < Lx/2) * + (-Ly/2 <= y < Ly/2) * + (-Lz/2 <= z < Lz/2) * + np.cos(np.sqrt(2) * + np.pi / Lx * c * t)) + + x = i*dx + lo[0] + y = j*dy + lo[1] + z = (k+0.5)*dz + lo[2] + Bz_th[i, j, k] = mu_0*(np.cos(m * pi/Lx * (x - Lx/2)) * + np.cos(n * pi/Ly * (y - Ly/2)) * + np.sin(p * pi/Lz * (z - Lz/2)) * + (-Lx/2 <= x < Lx/2) * + (-Ly/2 <= y < Ly/2) * + (-Lz/2 <= z < Lz/2) * + np.cos(np.sqrt(2) * np.pi / Lx * c * t)) + +# Open the right plot file +filename = sys.argv[1] +ds = yt.load(filename) +data = ds.covering_grid(level=0, left_edge=ds.domain_left_edge, dims=ds.domain_dimensions) + +rel_tol_err = 1e-1 + +# Compute relative l^2 error on By +By_sim = data['By'].to_ndarray() +rel_err_y = np.sqrt( np.sum(np.square(By_sim - By_th)) / np.sum(np.square(By_th))) +assert(rel_err_y < rel_tol_err) +# Compute relative l^2 error on Bz +Bz_sim = data['Bz'].to_ndarray() +rel_err_z = np.sqrt( np.sum(np.square(Bz_sim - Bz_th)) / np.sum(np.square(Bz_th))) +assert(rel_err_z < rel_tol_err) + +test_name = os.path.split(os.getcwd())[1] + +checksumAPI.evaluate_checksum(test_name, filename) diff --git a/Examples/Modules/embedded_boundary_cube/inputs_3d b/Examples/Modules/embedded_boundary_cube/inputs_3d new file mode 100644 index 000000000..481707540 --- /dev/null +++ b/Examples/Modules/embedded_boundary_cube/inputs_3d @@ -0,0 +1,37 @@ +stop_time = 1.3342563807926085e-08 +amr.n_cell = 48 48 48 +amr.max_grid_size = 128 +amr.max_level = 0 + +geometry.coord_sys = 0 +geometry.is_periodic = 0 0 0 +geometry.prob_lo = -0.8 -0.8 -0.8 +geometry.prob_hi = 0.8 0.8 0.8 +warpx.do_pml = 0 +warpx.const_dt = 1e-6 +warpx.cfl = 1 + +eb2.geom_type = box +eb2.box_lo = -0.5 -0.5 -0.5 +eb2.box_hi = 0.5 0.5 0.5 +eb2.box_has_fluid_inside = true + +warpx.B_ext_grid_init_style = parse_B_ext_grid_function +my_constants.m = 0 +my_constants.n = 1 +my_constants.p = 1 +my_constants.pi = 3.141592653589793 +my_constants.Lx = 1 +my_constants.Ly = 1 +my_constants.Lz = 1 +my_constants.h_2 = (m * pi / Lx) ** 2 + (n * pi / Ly) ** 2 + (p * pi / Lz) ** 2 +my_constants.mu_0 = 1.25663706212e-06 + +warpx.By_external_grid_function(x,y,z) = -2/h_2 * (n * pi / Ly) * (p * pi / Lz) * cos(m * pi / Lx * (x - Lx / 2)) * sin(n * pi / Ly * (y - Ly / 2)) * cos(p * pi / Lz * (z - Lz / 2))*mu_0*(x>-Lx/2)*(x<Lx/2)*(y>-Ly/2)*(y<Ly/2)*(z>-Lz/2)*(z<Lz/2) +warpx.Bx_external_grid_function(x,y,z) = -2/h_2 * (m * pi / Lx) * (p * pi / Lz) * sin(m * pi / Lx * (x - Lx / 2)) * cos(n * pi / Ly * (y - Ly / 2)) * cos(p * pi / Lz * (z - Lz / 2))*mu_0*(x>-Lx/2)*(x<Lx/2)*(y>-Ly/2)*(y<Ly/2)*(z>-Lz/2)*(z<Lz/2) +warpx.Bz_external_grid_function(x,y,z) = cos(m * pi / Lx * (x - Lx / 2)) * cos(n * pi / Ly * (y - Ly / 2)) * sin(p * pi / Lz * (z - Lz / 2))*mu_0*(x>-0.5)*(x<0.5)*(y>-0.5)*(y<0.5)*(z>-0.5)*(z<0.5) + +diagnostics.diags_names = diag1 +diag1.intervals = 1000 +diag1.diag_type = Full +diag1.fields_to_plot = Ex Ey Ez Bx By Bz |