############################################################################### # This file is part of SWIFT. # Copyright (c) 2025 Thomas Sandnes (thomas.d.sandnes@durham.ac.uk) # 2016 Matthieu Schaller (matthieu.schaller@durham.ac.uk) # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as published # by the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with this program. If not, see . # ############################################################################## import h5py import numpy as np import woma # Load EoS tables woma.load_eos_tables(["CD21_HHe", "AQUA"]) # Generates a swift IC file for the Rayleigh-Taylor instability test # Constants R_earth = 6371000 # Earth radius R_jupiter = 11.2089 * R_earth # Jupiter radius # Parameters N2_l = 64 # Number of particles along one edge in lower region N2_depth = 18 # Number of particles along in z dimension in lower region matID1 = 304 # Upper region material ID: AQUA matID2 = 307 # Lower region material ID: CD21 H--He rho1_approx = 9000 # Approximate density of upper region. To be recalculated rho2 = 3500 # Density of lower region g = -31.44 # Constant gravitational acceleration P0 = 3.2e12 # Pressure at interface boxsize_factor = 0.1 * R_jupiter dv = 0.00025 * boxsize_factor # Size of velocity perturbation boxsize_xy = [ 0.5 * boxsize_factor, 1.0 * boxsize_factor, ] # Size of the box in x and y dimensions boxsize_depth = boxsize_xy[0] * N2_depth / N2_l # Size of simulation box in z dimension fixed_region = [ 0.05 * boxsize_factor, 0.95 * boxsize_factor, ] # y-range of non fixed_region particles perturbation_region = [ 0.3 * boxsize_factor, 0.7 * boxsize_factor, ] # y-range for the velocity perturbation fileOutputName = "rayleigh_taylor.hdf5" # --------------------------------------------------- # Start by generating grids of particles of the two densities numPart2 = N2_l * N2_l * N2_depth numPart1 = int(numPart2 / rho2 * rho1_approx) N1_l = int(np.cbrt(boxsize_xy[0] * numPart1 / boxsize_depth)) N1_l -= N1_l % 4 # Make RT symmetric across centre of both instability regions N1_depth = int(boxsize_depth * N1_l / boxsize_xy[0]) numPart1 = int(N1_l * N1_l * N1_depth) numPart = numPart2 + numPart1 # Calculate particle masses and rho1 part_volume_l = (boxsize_xy[0] * 0.5 * boxsize_xy[1] * boxsize_depth) / numPart2 mass = rho2 * part_volume_l part_volume_h = (boxsize_xy[0] * 0.5 * boxsize_xy[1] * boxsize_depth) / numPart1 rho1 = mass / part_volume_h # Now construct two lattices of particles in the two regions A2_coords1 = np.empty((numPart1, 3)) A2_coords2 = np.empty((numPart2, 3)) A2_vel1 = np.zeros((numPart1, 3)) A2_vel2 = np.zeros((numPart2, 3)) A1_mat1 = np.full(numPart1, matID1) A1_mat2 = np.full(numPart2, matID2) A1_m1 = np.full(numPart1, mass) A1_m2 = np.full(numPart2, mass) A1_rho1 = np.full(numPart1, rho1) A1_rho2 = np.full(numPart2, rho2) A1_u1 = np.empty(numPart1) A1_u2 = np.empty(numPart2) A1_h1 = np.full(numPart1, boxsize_xy[0] / N1_l) A1_h2 = np.full(numPart2, boxsize_xy[0] / N2_l) A1_ids = np.zeros(numPart) # Set up boundary particle counter # Boundary particles are set by the N lowest ids of particles, where N is set when configuring swift boundary_particles = 1 # Particles in the upper region for i in range(N1_depth): for j in range(N1_l): for k in range(N1_l): index = i * N1_l ** 2 + j * N1_l + k A2_coords1[index, 0] = (j / float(N1_l) + 1.0 / (2.0 * N1_l)) * boxsize_xy[ 0 ] A2_coords1[index, 1] = (k / float(N1_l) + 1.0 / (2.0 * N1_l)) * ( 0.5 * boxsize_xy[1] ) + 0.5 * boxsize_xy[1] A2_coords1[index, 2] = ( i / float(N1_depth) + 1.0 / (2.0 * N1_depth) ) * boxsize_depth A1_rho1[index] = rho1 # If in top and bottom where particles are fixed if ( A2_coords1[index, 1] < fixed_region[0] or A2_coords1[index, 1] > fixed_region[1] ): A1_ids[index] = boundary_particles boundary_particles += 1 # Particles in the lower region for i in range(N2_depth): for j in range(N2_l): for k in range(N2_l): index = i * N2_l ** 2 + j * N2_l + k A2_coords2[index, 0] = (j / float(N2_l) + 1.0 / (2.0 * N2_l)) * boxsize_xy[ 0 ] A2_coords2[index, 1] = (k / float(N2_l) + 1.0 / (2.0 * N2_l)) * ( 0.5 * boxsize_xy[1] ) A2_coords2[index, 2] = ( i / float(N2_depth) + 1.0 / (2.0 * N2_depth) ) * boxsize_depth A1_rho2[index] = rho2 # If in top and bottom where particles are fixed if ( A2_coords2[index, 1] < fixed_region[0] or A2_coords2[index, 1] > fixed_region[1] ): A1_ids[index + numPart1] = boundary_particles boundary_particles += 1 print( "You need to compile the code with " "--enable-boundary-particles=%i" % boundary_particles ) # Set IDs of non-boundary particles A1_ids[A1_ids == 0] = np.linspace( boundary_particles, numPart, numPart - boundary_particles + 1 ) # The placement of the lattices are now adjusted to give appropriate interfaces # Calculate the separation of particles across the density discontinuity pcl_separation_2 = np.cbrt(mass / rho2) pcl_separation_1 = np.cbrt(mass / rho1) boundary_separation = 0.5 * (pcl_separation_2 + pcl_separation_1) # Shift top lattice min_y1 = min(A2_coords1[:, 1]) max_y2 = max(A2_coords2[:, 1]) shift_distance = boundary_separation - (min_y1 - max_y2) A2_coords1[:, 1] += shift_distance # Calculate internal energies A1_P1 = P0 + g * A1_rho1 * (A2_coords1[:, 1] - 0.5 * boxsize_xy[1]) A1_P2 = P0 + g * A1_rho2 * (A2_coords2[:, 1] - 0.5 * boxsize_xy[1]) A1_u1 = woma.A1_Z_rho_Y(A1_rho1, A1_P1, A1_mat1, Z_choice="u", Y_choice="P") A1_u2 = woma.A1_Z_rho_Y(A1_rho2, A1_P2, A1_mat2, Z_choice="u", Y_choice="P") # Now the two lattices can be combined A2_coords = np.append(A2_coords1, A2_coords2, axis=0) A2_vel = np.append(A2_vel1, A2_vel2, axis=0) A1_mat = np.append(A1_mat1, A1_mat2, axis=0) A1_m = np.append(A1_m1, A1_m2, axis=0) A1_rho = np.append(A1_rho1, A1_rho2, axis=0) A1_u = np.append(A1_u1, A1_u2, axis=0) A1_h = np.append(A1_h1, A1_h2, axis=0) # Add velocity perturbation mask_perturb = np.logical_and( A2_coords[:, 1] > perturbation_region[0], A2_coords[:, 1] < perturbation_region[1] ) A2_vel[mask_perturb, 1] = ( dv * (1 + np.cos(8 * np.pi * (A2_coords[mask_perturb, 0] / (boxsize_factor) + 0.25))) * (1 + np.cos(5 * np.pi * (A2_coords[mask_perturb, 1] / (boxsize_factor) - 0.5))) ) # Write ICs to file with h5py.File(fileOutputName, "w") as f: # Header grp = f.create_group("/Header") grp.attrs["BoxSize"] = [ boxsize_xy[0], boxsize_xy[1] + shift_distance, boxsize_depth, ] grp.attrs["NumPart_Total"] = [numPart, 0, 0, 0, 0, 0] grp.attrs["NumPart_Total_HighWord"] = [0, 0, 0, 0, 0, 0] grp.attrs["NumPart_ThisFile"] = [numPart, 0, 0, 0, 0, 0] grp.attrs["Time"] = 0.0 grp.attrs["NumFileOutputsPerSnapshot"] = 1 grp.attrs["MassTable"] = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0] grp.attrs["Flag_Entropy_ICs"] = [0, 0, 0, 0, 0, 0] grp.attrs["Dimension"] = 3 # Units grp = f.create_group("/Units") grp.attrs["Unit length in cgs (U_L)"] = 100.0 grp.attrs["Unit mass in cgs (U_M)"] = 1000.0 grp.attrs["Unit time in cgs (U_t)"] = 1.0 grp.attrs["Unit current in cgs (U_I)"] = 1.0 grp.attrs["Unit temperature in cgs (U_T)"] = 1.0 # Particle group grp = f.create_group("/PartType0") ds = grp.create_dataset("Coordinates", (numPart, 3), "d") ds[()] = A2_coords ds = grp.create_dataset("Velocities", (numPart, 3), "f") ds[()] = A2_vel ds = grp.create_dataset("Masses", (numPart, 1), "f") ds[()] = A1_m.reshape((numPart, 1)) ds = grp.create_dataset("Density", (numPart, 1), "f") ds[()] = A1_rho.reshape((numPart, 1)) ds = grp.create_dataset("SmoothingLength", (numPart, 1), "f") ds[()] = A1_h.reshape((numPart, 1)) ds = grp.create_dataset("InternalEnergy", (numPart, 1), "f") ds[()] = A1_u.reshape((numPart, 1)) ds = grp.create_dataset("ParticleIDs", (numPart, 1), "L") ds[()] = A1_ids.reshape((numPart, 1)) ds = grp.create_dataset("MaterialIDs", (numPart, 1), "i") ds[()] = A1_mat.reshape((numPart, 1))