├── tests ├── unit │ ├── test_dsmc │ │ ├── __init__.py │ │ ├── mesh │ │ │ ├── __init__.py │ │ │ └── mesh2d.py │ │ ├── common.py │ │ ├── diagnostics.py │ │ ├── dsmc.py │ │ ├── particles.py │ │ ├── boundary.py │ │ └── octree.py │ ├── main.py │ └── test_data │ │ ├── create_test_particles.py │ │ └── particles.csv ├── misc │ ├── T_sample.py │ ├── push_bound_test.py │ ├── push_bound_open_test.py │ ├── push_bound_inflow_test.py │ └── hypersonic_flow_mini.py ├── perfomance │ ├── integer.py │ ├── vector3d.py │ ├── vector.py │ └── pusher.py ├── diagnostics │ └── dia_test.py ├── octree │ └── octree_test.py └── domain │ ├── domain_obj.py │ └── boundary.py ├── dsmc ├── __init__.py ├── mesh │ ├── __init__.py │ └── mesh2d.py ├── writer │ ├── __init__.py │ ├── particles.py │ ├── planar.py │ └── octree.py ├── common.py ├── diagnostics.py ├── particles.py ├── boundary.py ├── octree.py └── dsmc.py ├── examples ├── heat_bath │ ├── heat_bath.png │ └── heat_bath.py ├── shock_tube │ ├── shock_tube.png │ ├── ref_data │ │ ├── sod_p.csv │ │ ├── sod_T.csv │ │ ├── sod_n.csv │ │ └── sod_rho.csv │ ├── plot.py │ ├── shock_tube.py │ └── tools │ │ └── sod_analytical.py └── hypersonic_flow │ ├── hypersonic_flow.png │ ├── hypersonic_flow_grid.png │ ├── hypersonic_flow_grid_nrho.png │ └── hypersonic_flow.py ├── setup.py ├── install_dependencies.sh ├── .circleci └── config.yml ├── CHANGELOG.md ├── .gitignore ├── doc ├── octree_resolution.ipynb └── Boundary.ipynb ├── README.md └── LICENSE /tests/unit/test_dsmc/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /dsmc/__init__.py: -------------------------------------------------------------------------------- 1 | from .dsmc import DSMC 2 | -------------------------------------------------------------------------------- /dsmc/mesh/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | -------------------------------------------------------------------------------- /tests/unit/test_dsmc/mesh/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | -------------------------------------------------------------------------------- /examples/heat_bath/heat_bath.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeoBasov/dsmc-python/HEAD/examples/heat_bath/heat_bath.png -------------------------------------------------------------------------------- /examples/shock_tube/shock_tube.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeoBasov/dsmc-python/HEAD/examples/shock_tube/shock_tube.png -------------------------------------------------------------------------------- /examples/hypersonic_flow/hypersonic_flow.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeoBasov/dsmc-python/HEAD/examples/hypersonic_flow/hypersonic_flow.png -------------------------------------------------------------------------------- /dsmc/writer/__init__.py: -------------------------------------------------------------------------------- 1 | from .octree import write_buttom_leafs 2 | from .planar import write as write_planar 3 | from .particles import write_positions 4 | -------------------------------------------------------------------------------- /examples/hypersonic_flow/hypersonic_flow_grid.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeoBasov/dsmc-python/HEAD/examples/hypersonic_flow/hypersonic_flow_grid.png -------------------------------------------------------------------------------- /examples/hypersonic_flow/hypersonic_flow_grid_nrho.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeoBasov/dsmc-python/HEAD/examples/hypersonic_flow/hypersonic_flow_grid_nrho.png -------------------------------------------------------------------------------- /dsmc/writer/particles.py: -------------------------------------------------------------------------------- 1 | def write_positions(particles, file_name="positions.csv"): 2 | with open(file_name, "w") as file: 3 | file.write("x, y, z\n") 4 | for pos in particles.Pos: 5 | file.write("{}, {}, {}\n".format(pos[0], pos[1], pos[2])) -------------------------------------------------------------------------------- /examples/shock_tube/ref_data/sod_p.csv: -------------------------------------------------------------------------------- 1 | 0.0, 100.0 2 | 0.040318868926081886, 100.0 3 | 0.05, 26.000000000001506 4 | 0.056144031805670194, 26.000000000001506 5 | 0.056144031805670194, 26.000000000001506 6 | 0.06582516287958831, 26.000000000001506 7 | 0.06582516287958831, 10.0 8 | 0.1, 10.0 9 | -------------------------------------------------------------------------------- /tests/unit/test_dsmc/common.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import dsmc.common as com 3 | import unittest 4 | 5 | class TestCommon(unittest.TestCase): 6 | def test_pass(self): 7 | box = np.array([[-1.0, 1.0], [-1.0, 1.0], [-1.0, 1.0]]) 8 | V = com.get_V(box) 9 | self.assertEqual(8.0, V) -------------------------------------------------------------------------------- /examples/shock_tube/ref_data/sod_T.csv: -------------------------------------------------------------------------------- 1 | 0.0, 300.00043556943234 2 | 0.040318868926081886, 300.00043556943234 3 | 0.05, 174.74734808382354 4 | 0.056144031805670194, 174.74734808382354 5 | 0.056144031805670194, 452.0973458360705 6 | 0.06582516287958831, 452.0973458360705 7 | 0.06582516287958831, 300.0004355694323 8 | 0.1, 300.0004355694323 9 | -------------------------------------------------------------------------------- /examples/shock_tube/ref_data/sod_n.csv: -------------------------------------------------------------------------------- 1 | 0.0, 2.41432e+22 2 | 0.040318868926081886, 2.41432e+22 3 | 0.05, 1.077654313396024e+22 4 | 0.056144031805670194, 1.077654313396024e+22 5 | 0.056144031805670194, 4.1654133816864355e+21 6 | 0.06582516287958831, 4.1654133816864355e+21 7 | 0.06582516287958831, 2.4143200000000005e+21 8 | 0.1, 2.4143200000000005e+21 9 | -------------------------------------------------------------------------------- /examples/shock_tube/ref_data/sod_rho.csv: -------------------------------------------------------------------------------- 1 | 0.0, 0.0016036396304 2 | 0.040318868926081886, 0.0016036396304 3 | 0.05, 0.000715799548043907 4 | 0.056144031805670194, 0.000715799548043907 5 | 0.056144031805670194, 0.0002766750876383764 6 | 0.06582516287958831, 0.0002766750876383764 7 | 0.06582516287958831, 0.00016036396304000002 8 | 0.1, 0.00016036396304000002 9 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | from setuptools import setup 2 | setup( 3 | name='dsmc', 4 | version='0.10.1', 5 | author='Leo Basov', 6 | python_requires='>=3.10, <4', 7 | packages=["dsmc", "dsmc.writer", "dsmc.mesh"], 8 | install_requires=[ 9 | 'numpy', 10 | 'llvmlite', 11 | 'scipy', 12 | 'numba' 13 | ], 14 | ) 15 | -------------------------------------------------------------------------------- /tests/unit/main.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | 3 | import unittest 4 | 5 | from test_dsmc.dsmc import * 6 | from test_dsmc.particles import * 7 | from test_dsmc.octree import * 8 | from test_dsmc.diagnostics import * 9 | from test_dsmc.common import * 10 | from test_dsmc.mesh.mesh2d import * 11 | from test_dsmc.boundary import * 12 | 13 | if __name__ == '__main__': 14 | unittest.main() 15 | -------------------------------------------------------------------------------- /install_dependencies.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | sudo apt update 4 | 5 | sudo apt install -y python3 6 | sudo apt install -y python3-pip 7 | sudo apt install -y python3-dbg 8 | 9 | pip3 install --upgrade pip setuptools wheel 10 | 11 | pip3 install numpy 12 | pip3 install llvmlite 13 | pip3 install scipy 14 | pip3 install numba 15 | pip3 install pytest 16 | 17 | echo "INSTALLATION COMPLETE" 18 | -------------------------------------------------------------------------------- /tests/unit/test_data/create_test_particles.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | if __name__ == "__main__": 4 | N = 100 5 | print("writing {} particles".format(N)) 6 | with open("particles.csv", "w") as file: 7 | for i in range(N): 8 | pos = np.random.random(3)*2.0 - np.ones(3) 9 | file.write("{},{},{}\n".format(pos[0], pos[1], pos[2])) 10 | 11 | print("done") -------------------------------------------------------------------------------- /tests/unit/test_dsmc/diagnostics.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import dsmc.diagnostics as dia 3 | import unittest 4 | 5 | class TestDiagnostics(unittest.TestCase): 6 | def test_sort_bin(self): 7 | positions = np.array(([1, 2, 3], [9, 8, 7], [10, 11, 12], [4, 5, 6])) 8 | Nbins = 4 9 | 10 | bins1, box, x = dia.sort_bin(positions, 0, Nbins) 11 | 12 | self.assertEqual(Nbins, len(bins1)) 13 | 14 | for b in bins1: 15 | self.assertEqual(1, len(b)) 16 | 17 | self.assertEqual(0, bins1[0][0]) 18 | self.assertEqual(3, bins1[1][0]) 19 | self.assertEqual(1, bins1[2][0]) 20 | self.assertEqual(2, bins1[3][0]) 21 | -------------------------------------------------------------------------------- /dsmc/common.py: -------------------------------------------------------------------------------- 1 | from numba import cfunc, njit 2 | import numba 3 | import numpy.typing as npt 4 | 5 | @cfunc("double(double[::3, ::2])") 6 | def get_V(a): 7 | return (a[0][1] - a[0][0]) * (a[1][1] - a[1][0]) * (a[2][1] - a[2][0]) 8 | 9 | @njit((numba.int64[:], numba.int64, numba.int64), cache=True) 10 | def swap(arr, pos1, pos2): 11 | temp = arr[pos2] 12 | arr[pos2] = arr[pos1] 13 | arr[pos1] = temp 14 | 15 | @njit(cache=True) 16 | def is_inside(position : npt.NDArray, box : npt.NDArray) -> bool: 17 | a : bool = position[0] >= box[0][0] and position[0] <= box[0][1] 18 | b : bool = position[1] >= box[1][0] and position[1] <= box[1][1] 19 | c : bool = position[2] >= box[2][0] and position[2] <= box[2][1] 20 | 21 | return a and b and c -------------------------------------------------------------------------------- /.circleci/config.yml: -------------------------------------------------------------------------------- 1 | version: 2.1 2 | 3 | commands: 4 | set_up_build_environment: 5 | steps: 6 | - checkout 7 | - run: 8 | name: Installing SUDO 9 | command: 'apt-get update && apt install -y sudo && rm -rf /var/lib/apt/lists/*' 10 | - run: 11 | name: Run INSTALL DEPENDENCIES 12 | command: bash install_dependencies.sh 13 | - run: 14 | name: Install DSMC 15 | command: pip3 install . 16 | 17 | run_unit_tests: 18 | steps: 19 | - run: 20 | name: Run UNIT TESTS 21 | command: cd tests/unit/ && python3 main.py -v 22 | 23 | executors: 24 | docker-jammy: 25 | docker: 26 | - image: "ubuntu:jammy" 27 | 28 | jobs: 29 | unit_tests: 30 | executor: docker-jammy 31 | steps: 32 | - set_up_build_environment 33 | - run_unit_tests 34 | 35 | workflows: 36 | build-and-run-tests: 37 | jobs: 38 | - unit_tests 39 | -------------------------------------------------------------------------------- /tests/misc/T_sample.py: -------------------------------------------------------------------------------- 1 | import dsmc 2 | import dsmc.particles as prt 3 | import matplotlib.pyplot as plt 4 | import numpy as np 5 | import math 6 | 7 | def maxwell(x, T): 8 | return 2.0 * np.sqrt(x) * np.exp(-x/T) / (math.pow(T, 3.0/2.0) * np.sqrt(math.pi)) 9 | 10 | def calc_x(velocities, mass): 11 | return np.array([mass*vel.dot(vel)/(2.0*prt.kb) for vel in velocities]) 12 | 13 | if __name__ == '__main__': 14 | solver = dsmc.DSMC() 15 | domain = ((-0.1e-3, 0.1e-3), (-0.1e-3, 0.1e-3), (0, 50e-3)) 16 | w = 1e6 17 | mass = 6.6422e-26 18 | T = 300 19 | n = 1e+20 20 | Nbins = 100 21 | 22 | solver.set_domain(domain) 23 | solver.set_weight(w) 24 | solver.set_mass(mass) 25 | 26 | solver.create_particles(domain, T, n) 27 | 28 | print(prt.calc_temperature(solver.particles.Vel, mass)) 29 | 30 | x = calc_x(solver.particles.Vel, solver.mass) 31 | 32 | xm = np.linspace(0, 3500, 1000) 33 | dist = [maxwell(xi, 300) for xi in xm] 34 | 35 | plt.plot(xm, dist) 36 | plt.hist(x, Nbins, density=True) 37 | plt.show() 38 | -------------------------------------------------------------------------------- /tests/perfomance/integer.py: -------------------------------------------------------------------------------- 1 | import numba 2 | import time 3 | import numpy as np 4 | 5 | def func(N): 6 | res = 0 7 | 8 | for i in range(N): 9 | res += i 10 | 11 | return res 12 | 13 | @numba.njit(cache=True) 14 | def func_njit(N): 15 | res = 0 16 | 17 | for i in range(N): 18 | res += i 19 | 20 | return res 21 | 22 | @numba.njit(numba.int32(numba.int32), cache=True) 23 | def func_njit_sig(N): 24 | res = 0 25 | 26 | for i in range(N): 27 | res += i 28 | 29 | return res 30 | 31 | def time_f(f, N): 32 | t = time.time() 33 | f(N) 34 | return time.time() - t 35 | 36 | if __name__ == '__main__': 37 | N = 10000000 38 | 39 | t = time_f(func, N) 40 | t_njit = time_f(func_njit, N) 41 | t_njit_sig = time_f(func_njit_sig, N) 42 | 43 | print("base line: {:.3e} ".format(t/t)) 44 | print("njit / base line: {:.3e} ".format(t_njit/t)) 45 | print("njit + signature / base line: {:.3e} ".format(t_njit_sig/t)) 46 | print('done') -------------------------------------------------------------------------------- /tests/perfomance/vector3d.py: -------------------------------------------------------------------------------- 1 | import numba 2 | import time 3 | import numpy as np 4 | 5 | def func(v): 6 | N = len(v) 7 | 8 | for i in range(N): 9 | v[i] += v[i] 10 | 11 | return v 12 | 13 | @numba.njit(cache=True) 14 | def func_njit(v): 15 | N = len(v) 16 | 17 | for i in range(N): 18 | v[i] += v[i] 19 | 20 | return v 21 | 22 | @numba.njit(numba.float64[:, :](numba.float64[:, :]), cache=True) 23 | def func_njit_sig(v): 24 | N = len(v) 25 | 26 | for i in range(N): 27 | v[i] += v[i] 28 | 29 | return v 30 | 31 | def time_f(f, v): 32 | t = time.time() 33 | f(v) 34 | return time.time() - t 35 | 36 | if __name__ == '__main__': 37 | N = 100000 38 | v = np.random.random((N, 3)) 39 | 40 | t = time_f(func, v) 41 | t_njit = time_f(func_njit, v) 42 | t_njit_sig = time_f(func_njit_sig, v) 43 | 44 | print("base line: {:.3e} ".format(t/t)) 45 | print("njit / base line: {:.3e} ".format(t_njit/t)) 46 | print("njit + signature / base line: {:.3e} ".format(t_njit_sig/t)) 47 | print('done') -------------------------------------------------------------------------------- /tests/perfomance/vector.py: -------------------------------------------------------------------------------- 1 | import numba 2 | import time 3 | import numpy as np 4 | 5 | def func(v): 6 | res = 0.0 7 | N = len(v) 8 | 9 | for i in range(N): 10 | res += v[i] 11 | 12 | return res 13 | 14 | @numba.njit(cache=True) 15 | def func_njit(v): 16 | res = 0.0 17 | N = len(v) 18 | 19 | for i in range(N): 20 | res += v[i] 21 | 22 | return res 23 | 24 | @numba.njit(numba.float64(numba.float64[:]), cache=True) 25 | def func_njit_sig(v): 26 | res = 0.0 27 | N = len(v) 28 | 29 | for i in range(N): 30 | res += v[i] 31 | 32 | return res 33 | 34 | def time_f(f, v): 35 | t = time.time() 36 | f(v) 37 | return time.time() - t 38 | 39 | if __name__ == '__main__': 40 | N = 100000 41 | v = np.random.random(N) 42 | 43 | t = time_f(func, v) 44 | t_njit = time_f(func_njit, v) 45 | t_njit_sig = time_f(func_njit_sig, v) 46 | 47 | print("base line: {:.3e} ".format(t/t)) 48 | print("njit / base line: {:.3e} ".format(t_njit/t)) 49 | print("njit + signature / base line: {:.3e} ".format(t_njit_sig/t)) 50 | print('done') -------------------------------------------------------------------------------- /tests/misc/push_bound_test.py: -------------------------------------------------------------------------------- 1 | import dsmc 2 | import dsmc.octree as oc 3 | import dsmc.writer as wrt 4 | import numpy as np 5 | 6 | if __name__ == '__main__': 7 | # general parameters 8 | solver = dsmc.DSMC() 9 | tree = oc.Octree() 10 | domain = [(-0.5, 0.5), (-0.5, 0.5), (-0.5, 0.5)] 11 | positions = np.array([(-0.5, -0.5, -0.5), (0.5, 0.5, 0.5)]) 12 | dt = 1e-5 13 | w = 1e+17 14 | n = 1e18 15 | mass = 6.6422e-26 16 | T = 300 17 | niter = 300 18 | 19 | # setup solver 20 | solver.set_domain(domain) 21 | solver.set_weight(w) 22 | solver.set_mass(mass) 23 | 24 | solver.create_particles(domain, T, n) 25 | 26 | tree.build(positions) 27 | 28 | for it in range(niter): 29 | print("iteration {:4}/{:4}".format(it + 1, niter), end="\r", flush=True) 30 | solver.advance(dt, collisions=False, octree=False) 31 | 32 | with open("particles_{}.csv".format(it), "w") as file: 33 | file.write("x, y, z\n") 34 | for pos in solver.particles.Pos: 35 | file.write("{},{},{}\n".format(pos[0], pos[1], pos[2])) 36 | 37 | wrt.write_buttom_leafs(tree, "octree.vtu") 38 | 39 | 40 | print("done") -------------------------------------------------------------------------------- /tests/diagnostics/dia_test.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import dsmc.diagnostics as dia 3 | import dsmc.writer as wrt 4 | import time 5 | 6 | def create_particles(N, radius): 7 | positions = np.empty((N + 1, 3)) 8 | 9 | for i in range(N): 10 | phi = np.random.random() * 2.0 * np.pi 11 | theta = np.random.random() * np.pi 12 | r = np.random.normal(0.0, 0.01) 13 | theta1 = np.random.random() * np.pi - 0.5 * np.pi 14 | dis = np.array((r * np.sin(theta) * np.cos(phi), r * np.sin(theta) * np.sin(phi), r * np.cos(theta))) 15 | offset = np.array((radius * np.sin(theta1), radius * np.cos(theta1), 0.0)) 16 | 17 | dis += offset; 18 | positions[i] = dis 19 | 20 | positions[N] = np.array((0.0, -1.0, 0.0)) 21 | 22 | return positions 23 | 24 | if __name__ == "__main__": 25 | N = 10000 26 | radius = 1.0 27 | positions = create_particles(N, radius) 28 | 29 | # set up sort 30 | Nx = 100 31 | Ny = 100 32 | x0 = -1.5 33 | x1 = 1.5 34 | y0 = -1.5 35 | y1 = 1.5 36 | 37 | start_time = time.time() 38 | boxes, values = dia.analyse_2d(positions, x0, x1, y0, y1, Nx, Ny) 39 | print("--- %s seconds ---" % (time.time() - start_time)) 40 | 41 | print("writing to file") 42 | 43 | wrt.write_planar(boxes, values) 44 | 45 | print("done") -------------------------------------------------------------------------------- /tests/unit/test_dsmc/dsmc.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | import numpy as np 3 | from dsmc import dsmc as ds 4 | 5 | class TestDSMC(unittest.TestCase): 6 | def test_Constructor(self): 7 | ds.DSMC() 8 | 9 | def test__calc_prob(self): 10 | vel1 : np.ndarray = np.array([1.0, 2.0, 3.0]) 11 | vel2 : np.ndarray = np.array([1.0, 2.0, 3.0]) 12 | vel_rel = np.linalg.norm(vel1 - vel2) 13 | sigma_T : float = 1.0 14 | Vc : float = 1.0 15 | dt : float = 1.0 16 | w : float = 1.0 17 | N : int = 1 18 | 19 | res = ds._calc_prob(vel_rel, sigma_T, Vc, dt, w, N) 20 | 21 | self.assertEqual(np.linalg.norm(vel1 - vel2), res) 22 | 23 | def test__calc_post_col_vels(self): 24 | velocity1 : np.ndarray = np.array([1.0, 2.0, 3.0]) 25 | velocity2 : np.ndarray = np.array([1.0, 2.0, 3.0]) 26 | mass1 : float = 1.0 27 | mass2 : float = 1.0 28 | rel_vel_module : float = 1.0 29 | rand_number1 : float = 1.0 30 | rand_number2 : float = 1.0 31 | 32 | res = ds._calc_post_col_vels(velocity1, velocity2, mass1, mass2, rel_vel_module, rand_number1, rand_number2) 33 | 34 | self.assertEqual(1.5, res[0][0]) 35 | self.assertEqual(2.0, res[0][1]) 36 | self.assertEqual(3.0, res[0][2]) 37 | 38 | self.assertEqual(0.5, res[1][0]) 39 | self.assertEqual(2.0, res[1][1]) 40 | self.assertEqual(3.0, res[1][2]) 41 | -------------------------------------------------------------------------------- /CHANGELOG.md: -------------------------------------------------------------------------------- 1 | # Changelog 2 | All notable changes to this project will be documented in this file. 3 | 4 | The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), 5 | and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). 6 | 7 | ## [Unreleased] 8 | 9 | ## [0.10.1] - 2023-03-12 10 | ## Fixed 11 | - use of numba features for marginal performance increase 12 | 13 | ## [0.10.0] - 2022-10-12 14 | ## Added 15 | - possibility to have centre of mass as division point for the octree 16 | 17 | ## [0.9.0] - 2022-10-09 18 | ## Added 19 | - mesh2d as for diagnostic purposes 20 | - particle writer 21 | - docs 22 | - hypersonic test case 23 | - backup boundary module 24 | 25 | ## [0.8.0] - 2022-10-03 26 | ### Added 27 | - planar writer 28 | - planar diagnostic 29 | 30 | ## [0.7.0] - 2022-10-01 31 | ### Added 32 | - inflow boundary condition 33 | - open boundary condition 34 | 35 | ## [0.6.0] - 2022-09-28 36 | ### Added 37 | - functionality for aspect ratio check in octree 38 | 39 | ### Fixed 40 | - bug in temperature initialization 41 | - several bugs in octree 42 | 43 | ## [0.5.1] - 2022-09-24 44 | ### Fixed 45 | - bugs in octree module 46 | 47 | ## [0.5.0] - 2022-09-23 48 | ### Added 49 | - writer module 50 | 51 | ## [0.4.0] - 2022-09-23 52 | ### Added 53 | - dsmc module 54 | 55 | ## [0.3.0] - 2022-09-22 56 | ### Added 57 | - octree module 58 | 59 | ## [0.2.0] - 2022-09-15 60 | ### Added 61 | - particle module 62 | 63 | ## [0.1.0] - 2022-09-15 64 | ### Added 65 | - unit test environment 66 | - cirlce ci integration 67 | - dependency installation script 68 | - dsmc module installation file 69 | -------------------------------------------------------------------------------- /tests/misc/push_bound_open_test.py: -------------------------------------------------------------------------------- 1 | import dsmc 2 | import dsmc.octree as oc 3 | import dsmc.writer as wrt 4 | import numpy as np 5 | 6 | if __name__ == '__main__': 7 | # general parameters 8 | solver = dsmc.DSMC() 9 | tree = oc.Octree() 10 | domain = [(-0.5, 0.5), (-0.5, 0.5), (-0.5, 0.5)] 11 | positions = np.array([(-0.5, -0.5, -0.5), (0.5, 0.5, 0.5)]) 12 | dt = 1e-5 13 | w = 1e+17 14 | n = 1e18 15 | mass = 6.6422e-26 16 | T = 300 17 | niter = 1000 18 | 19 | # setup solver 20 | solver.set_domain(domain) 21 | solver.set_weight(w) 22 | solver.set_mass(mass) 23 | 24 | solver.create_particles(domain, T, n) 25 | 26 | solver.set_bc_type("xmax", "open") 27 | solver.set_bc_type("xmin", "open") 28 | solver.set_bc_type("ymax", "open") 29 | solver.set_bc_type("ymin", "open") 30 | solver.set_bc_type("zmax", "open") 31 | solver.set_bc_type("zmin", "open") 32 | 33 | tree.build(positions) 34 | 35 | for it in range(niter): 36 | print("iteration {:4}/{:4}".format(it + 1, niter), end="\r", flush=True) 37 | 38 | try: 39 | solver.advance(dt, collisions=False, octree=False) 40 | except Exception as e: 41 | print(e) 42 | break 43 | 44 | with open("particles_{}.csv".format(it), "w") as file: 45 | file.write("x, y, z\n") 46 | for pos in solver.particles.Pos: 47 | file.write("{},{},{}\n".format(pos[0], pos[1], pos[2])) 48 | 49 | wrt.write_buttom_leafs(tree, "octree.vtu") 50 | 51 | 52 | print("done") -------------------------------------------------------------------------------- /tests/misc/push_bound_inflow_test.py: -------------------------------------------------------------------------------- 1 | import dsmc 2 | import dsmc.octree as oc 3 | import dsmc.writer as wrt 4 | import numpy as np 5 | 6 | if __name__ == '__main__': 7 | # general parameters 8 | solver = dsmc.DSMC() 9 | tree = oc.Octree() 10 | domain = [(-0.5, 0.5), (-0.5, 0.5), (-0.5, 0.5)] 11 | positions = np.array([(-0.5, -0.5, -0.5), (0.5, 0.5, 0.5)]) 12 | dt = 1e-5 13 | w = 1e+16 14 | n = 1e18 15 | u = np.array([1000.0, 0.0, 0.0]) 16 | mass = 6.6422e-26 17 | T = 300 18 | niter = 1000 19 | 20 | # setup solver 21 | solver.set_domain(domain) 22 | solver.set_weight(w) 23 | solver.set_mass(mass) 24 | 25 | solver.create_particles(domain, T, n) 26 | 27 | solver.set_bc_type("xmax", "open") 28 | 29 | solver.set_bc_type("ymax", "open") 30 | solver.set_bc_type("ymin", "open") 31 | solver.set_bc_type("zmax", "open") 32 | solver.set_bc_type("zmin", "open") 33 | 34 | solver.set_bc_type("xmin", "inflow") 35 | 36 | solver.set_bc_values("xmin", T, n, u) 37 | 38 | tree.build(positions) 39 | 40 | for it in range(niter): 41 | print("iteration {:4}/{:4}".format(it + 1, niter), end="\r", flush=True) 42 | 43 | try: 44 | solver.advance(dt, collisions=False, octree=False) 45 | except Exception as e: 46 | print(e) 47 | break 48 | 49 | with open("particles_{}.csv".format(it), "w") as file: 50 | file.write("x, y, z\n") 51 | for pos in solver.particles.Pos: 52 | file.write("{},{},{}\n".format(pos[0], pos[1], pos[2])) 53 | 54 | wrt.write_buttom_leafs(tree, "octree.vtu") 55 | 56 | 57 | print("done") -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | *.egg-info/ 24 | .installed.cfg 25 | *.egg 26 | MANIFEST 27 | 28 | # PyInstaller 29 | # Usually these files are written by a python script from a template 30 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 31 | *.manifest 32 | *.spec 33 | 34 | # Installer logs 35 | pip-log.txt 36 | pip-delete-this-directory.txt 37 | 38 | # Unit test / coverage reports 39 | htmlcov/ 40 | .tox/ 41 | .coverage 42 | .coverage.* 43 | .cache 44 | nosetests.xml 45 | coverage.xml 46 | *.cover 47 | .hypothesis/ 48 | .pytest_cache/ 49 | 50 | # Translations 51 | *.mo 52 | *.pot 53 | 54 | # Django stuff: 55 | *.log 56 | local_settings.py 57 | db.sqlite3 58 | 59 | # Flask stuff: 60 | instance/ 61 | .webassets-cache 62 | 63 | # Scrapy stuff: 64 | .scrapy 65 | 66 | # Sphinx documentation 67 | docs/_build/ 68 | 69 | # PyBuilder 70 | target/ 71 | 72 | # Jupyter Notebook 73 | .ipynb_checkpoints 74 | 75 | # pyenv 76 | .python-version 77 | 78 | # celery beat schedule file 79 | celerybeat-schedule 80 | 81 | # SageMath parsed files 82 | *.sage.py 83 | 84 | # Environments 85 | .env 86 | .venv 87 | env/ 88 | venv/ 89 | ENV/ 90 | env.bak/ 91 | venv.bak/ 92 | 93 | # Spyder project settings 94 | .spyderproject 95 | .spyproject 96 | 97 | # Rope project settings 98 | .ropeproject 99 | 100 | # mkdocs documentation 101 | /site 102 | 103 | # mypy 104 | .mypy_cache/ 105 | -------------------------------------------------------------------------------- /examples/shock_tube/plot.py: -------------------------------------------------------------------------------- 1 | import matplotlib.pyplot as plt 2 | import csv 3 | import numpy as np 4 | 5 | def read_data(file_name): 6 | with open(file_name) as file: 7 | reader = csv.reader(file, delimiter=',') 8 | 9 | for line in reader: 10 | l = [m for m in line if m] 11 | data = [float(l[i]) for i in range(len(l))] 12 | 13 | return data 14 | 15 | def read_ref_data(file_name): 16 | x = [] 17 | val = [] 18 | with open(file_name) as file: 19 | reader = csv.reader(file, delimiter=',') 20 | 21 | for line in reader: 22 | x.append(float(line[0])) 23 | val.append(float(line[1])) 24 | 25 | return x, val 26 | 27 | if __name__ == '__main__': 28 | n = read_data("n.csv") 29 | p = read_data("p.csv") 30 | T = read_data("T.csv") 31 | 32 | x_n, n_ref = read_ref_data("ref_data/sod_n.csv") 33 | p_n, p_ref = read_ref_data("ref_data/sod_p.csv") 34 | T_n, T_ref = read_ref_data("ref_data/sod_T.csv") 35 | 36 | fig, (ax0, ax1, ax2) = plt.subplots(nrows=1, ncols=3, figsize=(20, 6)) 37 | 38 | ax0.plot(np.linspace(0, 0.1, len(n)), n) 39 | ax0.plot(x_n, n_ref) 40 | ax0.set_xlim([0, 0.1]) 41 | ax0.set_ylim([0, 3e+22]) 42 | ax0.set_title("number denisty") 43 | ax0.set_xlabel("L / m") 44 | ax0.set_ylabel("n / m^(-3)") 45 | 46 | ax1.plot(np.linspace(0, 0.1, len(n)), T) 47 | ax1.plot(T_n, T_ref) 48 | ax1.set_xlim([0, 0.1]) 49 | ax1.set_ylim([150, 500]) 50 | ax1.set_title("temperature") 51 | ax1.set_xlabel("L / m") 52 | ax1.set_ylabel("T / K") 53 | 54 | ax2.plot(np.linspace(0, 0.1, len(n)), p) 55 | ax2.plot(p_n, p_ref) 56 | ax2.set_xlim([0, 0.1]) 57 | ax2.set_ylim([0, 120]) 58 | ax2.set_title("pressure") 59 | ax2.set_xlabel("L / m") 60 | ax2.set_ylabel("p / Pa") 61 | 62 | plt.show() 63 | -------------------------------------------------------------------------------- /doc/octree_resolution.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "id": "9db716f6-c301-4d2e-b06f-19cd98de2e5f", 7 | "metadata": {}, 8 | "outputs": [], 9 | "source": [ 10 | "import math" 11 | ] 12 | }, 13 | { 14 | "cell_type": "markdown", 15 | "id": "772d42fa-dc37-48e9-a599-392077582e98", 16 | "metadata": {}, 17 | "source": [ 18 | "The mean free path can be written as\n", 19 | "$$\n", 20 | "\\lambda = \\frac{1}{\\sqrt{2} \\cdot n_{c} \\cdot \\sigma_T}\n", 21 | "$$\n", 22 | "where $n_c$ is the number density in the cell and $\\sigma_T$ is the total cross section.\n", 23 | "The number of particles in cell $N_{c}$ can be calculated as (asuming cubic cells)\n", 24 | "$$\n", 25 | "N_{c} = \\frac{1}{w} \\cdot L_c^3 \\cdot n_c\n", 26 | "$$\n", 27 | "where $L_C$ is the side length of the cell and $w$ being the particle weight.\n", 28 | "Assuming that the cell side fullfills the criteria\n", 29 | "$$\n", 30 | "\\frac{L_c}{\\lambda} \\leq \\frac{1}{2}.\n", 31 | "$$\n", 32 | "This leads to the criterium\n", 33 | "$$\n", 34 | "N \\leq \\frac{\\sqrt{2}}{32 \\cdot w \\cdot \\sigma^2_T \\cdot n^3_c}\n", 35 | "$$" 36 | ] 37 | }, 38 | { 39 | "cell_type": "code", 40 | "execution_count": null, 41 | "id": "4f03b0f7-64a9-48e5-989c-2e253ce09c1d", 42 | "metadata": {}, 43 | "outputs": [], 44 | "source": [] 45 | } 46 | ], 47 | "metadata": { 48 | "kernelspec": { 49 | "display_name": "Python 3 (ipykernel)", 50 | "language": "python", 51 | "name": "python3" 52 | }, 53 | "language_info": { 54 | "codemirror_mode": { 55 | "name": "ipython", 56 | "version": 3 57 | }, 58 | "file_extension": ".py", 59 | "mimetype": "text/x-python", 60 | "name": "python", 61 | "nbconvert_exporter": "python", 62 | "pygments_lexer": "ipython3", 63 | "version": "3.9.12" 64 | } 65 | }, 66 | "nbformat": 4, 67 | "nbformat_minor": 5 68 | } 69 | -------------------------------------------------------------------------------- /examples/shock_tube/shock_tube.py: -------------------------------------------------------------------------------- 1 | import dsmc 2 | import dsmc.diagnostics as dia 3 | import time 4 | 5 | def write2file(solver, Nbins): 6 | # open files 7 | n_file = open("n.csv", "w") 8 | T_file = open("T.csv", "w") 9 | p_file = open("p.csv", "w") 10 | 11 | bins, box, x = dia.sort_bin(solver.particles.Pos, 2, Nbins) 12 | n = dia.calc_n(bins, box, 2, solver.w) 13 | T = dia.calc_T(bins, solver.particles.Vel, mass) 14 | p = dia.calc_p(n, T) 15 | 16 | for i in range(Nbins): 17 | n_file.write("{},".format(n[i])) 18 | T_file.write("{},".format(T[i])) 19 | p_file.write("{},".format(p[i])) 20 | 21 | n_file.write("\n") 22 | T_file.write("\n") 23 | p_file.write("\n") 24 | 25 | # close files 26 | n_file.close() 27 | T_file.close() 28 | p_file.close() 29 | 30 | if __name__ == '__main__': 31 | # general parameters 32 | solver = dsmc.DSMC() 33 | domain = [(-0.0001, 0.0001), (-0.0001, 0.0001), (0.0, 0.1)] 34 | dt = 1e-7 35 | w = 1e+8 36 | mass = 6.6422e-26 37 | niter = 300 38 | Nbins = 1000 39 | 40 | # high denisty particles 41 | nhigh = 2.41432e+22 42 | Thigh = 300 43 | Boxhigh = [(-0.0001, 0.0001), (-0.0001, 0.0001), (0.0, 0.05)] 44 | 45 | # low denisty particles 46 | nlow = nhigh*0.1 47 | Tlow = 300 48 | Boxlow = [(-0.0001, 0.0001), (-0.0001, 0.0001), (0.05, 0.1)] 49 | 50 | # setup solver 51 | solver.set_domain(domain) 52 | solver.set_weight(w) 53 | solver.set_mass(mass) 54 | 55 | solver.create_particles(Boxlow, Tlow, nlow) 56 | solver.create_particles(Boxhigh, Thigh, nhigh) 57 | 58 | # start timing 59 | start_time = time.time() 60 | 61 | for it in range(niter): 62 | print("iteration {:4}/{}".format(it + 1, niter), end="\r", flush=True) 63 | solver.advance(dt) 64 | 65 | print("") 66 | print("--- %s seconds ---" % (time.time() - start_time)) 67 | 68 | write2file(solver, Nbins) 69 | 70 | print('done') 71 | -------------------------------------------------------------------------------- /tests/misc/hypersonic_flow_mini.py: -------------------------------------------------------------------------------- 1 | import dsmc 2 | import dsmc.writer as wrt 3 | import dsmc.octree as oc 4 | import time 5 | import numpy as np 6 | 7 | if __name__ == '__main__': 8 | # general parameters 9 | solver = dsmc.DSMC() 10 | domain = [(-3.0, 3.0), (-1.5, 1.5), (-0.025, 0.025)] 11 | obj = [(-0.25, 0.25), (-0.25, 0.25), (-0.5, 0.5)] 12 | dt = 1e-6 13 | w = 0.2 * 2.3e+15 14 | mass = 6.6422e-26 15 | T = 273.0 16 | n = 2.6e+19 17 | u = np.array([0.0, -3043.0, 0.0]) 18 | niter = 500 19 | 20 | h = domain[2][1] - domain[2][0] 21 | 22 | # setup solver 23 | solver.set_domain(domain) 24 | solver.set_weight(w) 25 | solver.set_mass(mass) 26 | 27 | # set object 28 | solver.add_object(obj) 29 | 30 | # trees 31 | tree_inner = oc.Octree() 32 | tree_outer = oc.Octree() 33 | 34 | inner_pos = np.array([[-0.25, -0.25, -0.025], [0.25, 0.25, 0.025]]) 35 | outer_pos = np.array([[-3.0, -1.5, -0.025], [3.0, 1.5, 0.025]]) 36 | 37 | tree_inner.build(inner_pos) 38 | tree_outer.build(outer_pos) 39 | 40 | # create particles 41 | positions = np.zeros((2, 3)) 42 | velocities = np.zeros((2, 3)) 43 | 44 | positions[0][0] = -0.01 45 | positions[0][1] = 1.4 46 | positions[0][2] = -0.01 47 | 48 | positions[1][0] = 0.01 49 | positions[1][1] = 1.3 50 | positions[1][2] = 0.01 51 | 52 | velocities[0][1] = -3043.0 53 | velocities[1][1] = -3043.0 54 | 55 | solver.particles.VelPos = (velocities, positions) 56 | 57 | # start timing 58 | start_time = time.time() 59 | 60 | for it in range(niter): 61 | print("iteration {:4}/{}".format(it + 1, niter), end="\r", flush=True) 62 | solver.advance(dt) 63 | wrt.write_positions(solver.particles, "pos_{}.csv".format(it)) 64 | 65 | wrt.write_buttom_leafs(tree_inner, "innter.vtu") 66 | wrt.write_buttom_leafs(tree_outer, "outer.vtu") 67 | 68 | print("") 69 | print("--- %s seconds ---" % (time.time() - start_time)) 70 | print('done') -------------------------------------------------------------------------------- /tests/octree/octree_test.py: -------------------------------------------------------------------------------- 1 | import dsmc.writer as wrt 2 | import dsmc.octree as oc 3 | import numpy as np 4 | import argparse 5 | 6 | def create_particles(N, radius): 7 | positions = np.empty((N + 1, 3)) 8 | 9 | for i in range(N): 10 | phi = np.random.random() * 2.0 * np.pi 11 | theta = np.random.random() * np.pi 12 | r = np.random.normal(0.0, 0.01) 13 | theta1 = np.random.random() * np.pi - 0.5 * np.pi 14 | dis = np.array((r * np.sin(theta) * np.cos(phi), r * np.sin(theta) * np.sin(phi), r * np.cos(theta))) 15 | offset = np.array((radius * np.sin(theta1), radius * np.cos(theta1), 0.0)) 16 | 17 | dis += offset; 18 | positions[i] = dis 19 | 20 | positions[N] = np.array((0.0, -1.0, 0.0)) 21 | 22 | return positions 23 | 24 | if __name__ == "__main__": 25 | parser = argparse.ArgumentParser(description='Process some integers.') 26 | parser.add_argument('N', type=int) 27 | 28 | args = parser.parse_args() 29 | 30 | radius = 1.0 31 | positions = create_particles(args.N, radius) 32 | octree = oc.Octree() 33 | octree.build(positions) 34 | wrt.write_buttom_leafs(octree) 35 | 36 | for i in range(len(octree.leafs)): 37 | box = octree.cell_boxes[i] 38 | leaf = octree.leafs[i] 39 | N = 0 40 | for j in range(leaf.elem_offset, leaf.elem_offset + leaf.number_elements): 41 | p = octree.permutations[j] 42 | pos = positions[p] 43 | 44 | if oc._is_inside(pos, box): 45 | N += 1 46 | else: 47 | raise Exception(pos, box) 48 | 49 | if N != leaf.number_elements: 50 | raise Exception(N, leaf.number_elements, box) 51 | 52 | with open("particles.csv", "w") as file: 53 | file.write("x, y, z\n") 54 | 55 | for i in range(len(octree.leafs)): 56 | leaf = octree.leafs[i] 57 | if leaf.number_children == 0 and leaf.number_elements > 0: 58 | for j in range(leaf.elem_offset, leaf.elem_offset + leaf.number_elements): 59 | p = octree.permutations[j] 60 | pos = positions[p] 61 | file.write("{}, {}, {}\n".format(pos[0], pos[1], pos[2])) 62 | 63 | print("done") 64 | -------------------------------------------------------------------------------- /tests/perfomance/pusher.py: -------------------------------------------------------------------------------- 1 | import numba 2 | import numpy as np 3 | import time 4 | 5 | def _push(velocities, positions, dt): 6 | old_positions = np.copy(positions) 7 | for p in numba.prange(len(positions)): 8 | positions[p] = positions[p] + velocities[p]*dt 9 | return (velocities, positions, old_positions) 10 | 11 | def push(velocities, positions, dt): 12 | N = len(positions) 13 | for p in numba.prange(N): 14 | positions[p] = positions[p] + velocities[p]*dt 15 | return positions 16 | 17 | @numba.njit(cache=True) 18 | def push_njit(velocities, positions, dt): 19 | N = len(positions) 20 | for p in numba.prange(N): 21 | positions[p] = positions[p] + velocities[p]*dt 22 | return positions 23 | 24 | @numba.njit(numba.float64[:, :](numba.float64[:, :], numba.float64[:, :], numba.float64), cache=True) 25 | def push_njit_sig(velocities, positions, dt): 26 | N = len(positions) 27 | for p in numba.prange(N): 28 | positions[p] = positions[p] + velocities[p]*dt 29 | return positions 30 | 31 | @numba.njit(numba.float64[:, :](numba.float64[:, :], numba.float64[:, :], numba.float64), cache=True, parallel=True) 32 | def push_njit_sig_par(velocities, positions, dt): 33 | N = len(positions) 34 | for p in numba.prange(N): 35 | positions[p] += velocities[p]*dt 36 | return positions 37 | 38 | def time_f(f, v, p, dt): 39 | t = time.time() 40 | f(v, p, dt) 41 | return time.time() - t 42 | 43 | if __name__ == '__main__': 44 | N = 100000 45 | v = np.random.random((N, 3)) 46 | p = np.random.random((N, 3)) 47 | dt = 1e-6 48 | 49 | t = time_f(_push, v, p, dt) 50 | t_new = time_f(push, v, p, dt) 51 | t_njit = time_f(push_njit, v, p, dt) 52 | t_njit_sig = time_f(push_njit_sig, v, p, dt) 53 | t_njit_sig_par = time_f(push_njit_sig_par, v, p, dt) 54 | 55 | print("base line: {:.3e} ".format(t/t)) 56 | print("new / base line: {:.3e} ".format(t_new/t)) 57 | print("new / base line: {:.3e} ".format(t_njit/t)) 58 | print("njit + signature / base line: {:.3e} ".format(t_njit_sig/t)) 59 | print("njit + signature + par / base line: {:.3e} ".format(t_njit_sig_par/t)) 60 | print('done') -------------------------------------------------------------------------------- /examples/heat_bath/heat_bath.py: -------------------------------------------------------------------------------- 1 | import dsmc 2 | import dsmc.particles as prt 3 | import matplotlib.pyplot as plt 4 | import numpy as np 5 | import numba 6 | import math 7 | import time 8 | 9 | @numba.njit(numba.float64(numba.float64, numba.float64)) 10 | def maxwell(x, T): 11 | return 2.0 * np.sqrt(x) * np.exp(-x/T) / (math.pow(T, 3.0/2.0) * np.sqrt(math.pi)) 12 | 13 | @numba.njit(numba.float64[:](numba.float64[:, :], numba.float64)) 14 | def calc_x(velocities, mass): 15 | return np.array([mass*vel.dot(vel)/(2.0*prt.kb) for vel in velocities]) 16 | 17 | if __name__ == '__main__': 18 | # general parameters 19 | solver = dsmc.DSMC() 20 | domain = ((-1.0e-3, 1.0e-3), (-1.0e-3, 1.0e-3), (-1.0e-3, 1.0e-3)) 21 | dt = 1e-5 22 | w = 0.5e+8 23 | mass = 6.6422e-26 24 | niter = 100 25 | Nbins = 200 26 | 27 | # particles 28 | n = 1.0e+20 29 | T = 300 30 | u = np.array((1000.0, 0.0, 0.0)) 31 | 32 | 33 | solver.set_domain(domain) 34 | solver.set_weight(w) 35 | solver.set_mass(mass) 36 | 37 | solver.create_particles(domain, T, n, u) 38 | 39 | # time 40 | start_time = time.time() 41 | 42 | # set up plot 43 | xmax = 15000 44 | 45 | Tnew = prt.calc_temperature(solver.particles.Vel, solver.mass) 46 | xm = np.linspace(0, xmax, 1000) 47 | dist = [maxwell(xi, Tnew) for xi in xm] 48 | x = calc_x(solver.particles.Vel, solver.mass) 49 | 50 | fig, (ax0, ax1) = plt.subplots(nrows=1, ncols=2, figsize=(16, 6)) 51 | 52 | ax0.plot(xm, dist) 53 | ax0.hist(x, Nbins, density=True) 54 | ax0.set_ylabel("probabilty density") 55 | ax0.set_xlabel("m v^2 / (2 kb)") 56 | ax0.set_title("initial condition") 57 | ax0.set_xlim([0, xmax]) 58 | ax0.set_ylim([0, 0.00040]) 59 | 60 | for it in range(niter): 61 | print("iteration {:4}/{}".format(it + 1, niter), end="\r", flush=True) 62 | solver.advance(dt) 63 | x = calc_x(solver.particles.Vel, solver.mass) 64 | 65 | print("") 66 | print("--- %s seconds ---" % (time.time() - start_time)) 67 | 68 | ax1.plot(xm, dist) 69 | ax1.hist(x, Nbins, density=True) 70 | ax1.set_ylabel("probabilty density") 71 | ax1.set_xlabel("m v^2 / (2 kb)") 72 | ax1.set_title("final condition") 73 | ax1.set_xlim([0, xmax]) 74 | ax1.set_ylim([0, 0.00040]) 75 | 76 | fig.suptitle("Argon Heat Bath") 77 | plt.show() 78 | 79 | print('done') 80 | -------------------------------------------------------------------------------- /tests/domain/domain_obj.py: -------------------------------------------------------------------------------- 1 | import dsmc 2 | import dsmc.octree as oc 3 | import dsmc.writer as wrt 4 | import time 5 | import numpy as np 6 | 7 | def create_pos_and_vels(): 8 | positions = np.zeros((6, 3)) 9 | velocitiies = np.zeros((6, 3)) 10 | 11 | # x 12 | positions[0][0] = -0.75 13 | velocitiies[0][0] = 1.0 14 | 15 | positions[1][0] = 0.75 16 | velocitiies[1][0] = -1.0 17 | 18 | # y 19 | positions[2][1] = -0.75 20 | velocitiies[2][1] = 1.0 21 | 22 | positions[3][1] = 0.75 23 | velocitiies[3][1] = -1.0 24 | 25 | # z 26 | positions[4][2] = -0.75 27 | velocitiies[4][2] = 1.0 28 | 29 | positions[5][2] = 0.75 30 | velocitiies[5][2] = -1.0 31 | 32 | return (velocitiies, positions) 33 | 34 | def write_partices(positions, it): 35 | with open("particles_{}.csv".format(it), "w") as file: 36 | file.write("x, y, z\n") 37 | for pos in positions: 38 | file.write("{}, {}, {}\n".format(pos[0], pos[1], pos[2])) 39 | 40 | if __name__ == '__main__': 41 | # general parameters 42 | solver = dsmc.DSMC() 43 | domain = [(-1.0, 1.0), (-1.0, 1.0), (-1.0, 1.0)] 44 | obj = [(-0.5, 0.5), (-0.5, 0.5), (-0.5, 0.5)] 45 | dt = 0.01 46 | w = 2.3e+14 47 | mass = 6.6422e-26 48 | T = 273.0 49 | n = 2.6e+19 50 | niter = 200 51 | 52 | # trees 53 | tree_inner = oc.Octree() 54 | tree_outer = oc.Octree() 55 | 56 | inner_pos = np.array([[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]]) 57 | outer_pos = np.array([[-1.0, -1.0, -1.0], [1.0, 1.0, 1.0]]) 58 | 59 | tree_inner.build(inner_pos) 60 | tree_outer.build(outer_pos) 61 | 62 | # setup solver 63 | solver.set_domain(domain) 64 | solver.set_weight(w) 65 | solver.set_mass(mass) 66 | 67 | # set object 68 | solver.add_object(obj) 69 | 70 | # create particles 71 | solver.particles.VelPos = create_pos_and_vels() 72 | 73 | # start timing 74 | start_time = time.time() 75 | 76 | for it in range(niter): 77 | print("iteration {:4}/{}".format(it + 1, niter), end="\r", flush=True) 78 | solver.advance(dt, octree=False) 79 | write_partices(solver.particles.Pos, it) 80 | 81 | wrt.write_buttom_leafs(tree_inner, "inner_box.vtu") 82 | wrt.write_buttom_leafs(tree_outer, "outer_box.vtu") 83 | 84 | print("") 85 | print("--- %s seconds ---" % (time.time() - start_time)) 86 | print('done') -------------------------------------------------------------------------------- /dsmc/writer/planar.py: -------------------------------------------------------------------------------- 1 | def write(boxes, values, file_name="planar.vtu"): 2 | f = open(file_name, "w") 3 | 4 | _write_header(f) 5 | _wrtie_body(f, boxes, values) 6 | _write_footer(f) 7 | 8 | f.close() 9 | 10 | def _write_header(f): 11 | f.write("\n") 12 | 13 | def _wrtie_body(f, boxes, values): 14 | f.write("\n") 15 | f.write("\n".format(len(boxes) * 4, len(boxes))) 16 | 17 | _write_points(f, boxes) 18 | _write_cells(f, boxes) 19 | _write_cell_data(f, boxes, values) 20 | 21 | f.write("\n") 22 | f.write("\n") 23 | 24 | def _write_points(f, boxes): 25 | f.write("\n") 26 | f.write("\n") 27 | 28 | for box in boxes: 29 | f.write("{} ".format(box[0][0])) 30 | f.write("{} ".format(box[1][0])) 31 | f.write("{} ".format(0.0)) 32 | 33 | f.write("{} ".format(box[0][1])) 34 | f.write("{} ".format(box[1][0])) 35 | f.write("{} ".format(0.0)) 36 | 37 | f.write("{} ".format(box[0][1])) 38 | f.write("{} ".format(box[1][1])) 39 | f.write("{} ".format(0.0)) 40 | 41 | f.write("{} ".format(box[0][0])) 42 | f.write("{} ".format(box[1][1])) 43 | f.write("{} ".format(0.0)) 44 | 45 | f.write("\n") 46 | f.write("\n") 47 | 48 | 49 | def _write_cells(f, boxes): 50 | k = 0 51 | 52 | f.write("\n") 53 | f.write("\n") 54 | 55 | for i in range(len(boxes)): 56 | for _ in range(4): 57 | f.write("{} ".format(k)) 58 | k += 1 59 | 60 | f.write("\n") 61 | f.write("\n") 62 | 63 | for i in range(len(boxes)): 64 | f.write("{} ".format((i + 1) * 4)) 65 | 66 | f.write("\n") 67 | f.write("\n") 68 | 69 | for _ in range(len(boxes)): 70 | f.write("9 ") 71 | 72 | f.write("\n") 73 | f.write("\n") 74 | 75 | def _write_cell_data(f, boxes, values): 76 | f.write("\n") 77 | f.write("\n") 78 | 79 | for vals in values: 80 | f.write("{} ".format(vals.number_elements)) 81 | 82 | f.write("\n") 83 | f.write("\n") 84 | 85 | def _write_footer(f): 86 | f.write("\n") 87 | -------------------------------------------------------------------------------- /dsmc/diagnostics.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from . import particles as prt 3 | from . import octree as oc 4 | #from . import common as com 5 | 6 | class Values: 7 | def __init__(self): 8 | self.number_elements = 0 9 | 10 | def calc_vals(self, positions, velocities, ids, box): 11 | #V = com.get_V(box) 12 | self.number_elements = len(ids) 13 | 14 | 15 | def analyse_2d(positions, velocities, mesh2d, h): 16 | boxes = np.empty((len(mesh2d.cells), 3, 2)) 17 | values = [Values() for _ in range(len(mesh2d.cells))] 18 | 19 | for y in range(mesh2d.n_cells2): 20 | for x in range(mesh2d.n_cells1): 21 | N = x + y * mesh2d.n_cells1 22 | 23 | boxes[N][0][0] = mesh2d.min1 + mesh2d.cell_size1*x 24 | boxes[N][0][1] = mesh2d.min1 + mesh2d.cell_size1*(x + 1) 25 | boxes[N][1][0] = mesh2d.min2 + mesh2d.cell_size2*y 26 | boxes[N][1][1] = mesh2d.min2 + mesh2d.cell_size2*(y + 1) 27 | boxes[N][2][0] = 0.0 28 | boxes[N][2][1] = h 29 | 30 | values[N].calc_vals(positions, velocities, mesh2d.cells[N], boxes[N]) 31 | 32 | return (boxes, values) 33 | 34 | 35 | def sort_bin(positions, axis, Nbin): 36 | bins = [[] for _ in range(Nbin)] 37 | b = 0 38 | box = oc._find_bounding_box(positions) 39 | dx = (box[axis][1] - box[axis][0]) / (Nbin - 1) 40 | xx = [dx] 41 | x = dx 42 | sub_pos = np.array([pos[axis] for pos in positions]) 43 | sorted_pos = np.argsort(sub_pos) 44 | 45 | for i in range(len(sorted_pos)): 46 | p = sorted_pos[i] 47 | while positions[p][axis] > x: 48 | x += dx 49 | b += 1 50 | xx.append(x) 51 | 52 | bins[b].append(p) 53 | 54 | return bins, box, xx 55 | 56 | def calc_n(bins, box, axis, w): 57 | Nbins = len(bins) 58 | V = 1 59 | n = np.empty((Nbins, )) 60 | for i in range(3): 61 | if i == axis: 62 | V *= (box[i][1] - box[i][0]) / Nbins 63 | else: 64 | V *= (box[i][1] - box[i][0]) 65 | 66 | for i in range(Nbins): 67 | n[i] = len(bins[i]) * w / V 68 | 69 | return n 70 | 71 | def calc_T(bins, velocities, mass): 72 | Nbins = len(bins) 73 | T = np.empty((Nbins, )) 74 | 75 | for i in range(Nbins): 76 | vels = np.array([velocities[p] for p in bins[i]]) 77 | T[i] = prt.calc_temperature(vels, mass) 78 | 79 | return T 80 | 81 | def calc_p(n, T): 82 | Nbins = len(n) 83 | p = np.empty((Nbins, )) 84 | 85 | for i in range(Nbins): 86 | p[i] = n[i]*T[i]*prt.kb 87 | 88 | return p 89 | -------------------------------------------------------------------------------- /tests/domain/boundary.py: -------------------------------------------------------------------------------- 1 | import dsmc.dsmc as ds 2 | import dsmc.particles as prt 3 | import dsmc.octree as oc 4 | import dsmc.writer as wrt 5 | import dsmc.boundary as bo 6 | import dsmc.common as co 7 | import time 8 | import numpy as np 9 | 10 | def create_pos_and_vels(): 11 | positions = np.zeros((6, 3)) 12 | velocitiies = np.zeros((6, 3)) 13 | 14 | # x 15 | positions[0][0] = -0.75 16 | velocitiies[0][0] = 100.0 17 | 18 | positions[1][0] = 0.75 19 | velocitiies[1][0] = -100.0 20 | 21 | # y 22 | positions[2][1] = -0.75 23 | velocitiies[2][1] = 100.0 24 | 25 | positions[3][1] = 0.75 26 | velocitiies[3][1] = -100.0 27 | 28 | # z 29 | positions[4][2] = -0.75 30 | velocitiies[4][2] = 100.0 31 | 32 | positions[5][2] = 0.75 33 | velocitiies[5][2] = -100.0 34 | 35 | return (velocitiies, positions) 36 | 37 | if __name__ == '__main__': 38 | # general parameters 39 | boundary = bo.Boundary() 40 | particles = prt.Particles() 41 | domain = np.array([(-1.0, 1.0), (-1.0, 1.0), (-1.0, 1.0)]) 42 | dt = 0.0001 43 | w = 2.3e+16 44 | mass = 6.6422e-26 45 | T = 273.0 46 | n = 2.6e+19 47 | N = int(co.get_V(domain)*n/w) 48 | niter = 1000 49 | 50 | # trees 51 | tree_outer = oc.Octree() 52 | outer_pos = np.array([[-1.0, -1.0, -1.0], [1.0, 1.0, 1.0]]) 53 | tree_outer.build(outer_pos) 54 | #wrt.write_buttom_leafs(tree_outer, "outer_box.vtu") 55 | 56 | # setup solver 57 | boundary.domain = domain 58 | 59 | # create particles 60 | particles.create_particles(domain, mass, T, N) 61 | 62 | velocities, positions = particles.VelPos 63 | 64 | #particles.VelPos = create_pos_and_vels() 65 | 66 | # start timing 67 | start_time = time.time() 68 | 69 | wrt.write_positions(particles, "pos_{}.csv".format(0)) 70 | 71 | E0 = 0.0 72 | 73 | for vel in particles.Vel: 74 | E0 += vel.dot(vel) 75 | 76 | for it in range(niter): 77 | E = 0.0 78 | 79 | velocities, positions, old_positions = ds._push(particles.Vel, particles.Pos, dt) 80 | velocities, positions, old_positions = boundary.boundary(velocities, positions, old_positions) 81 | 82 | particles.VelPos = (velocities, positions) 83 | wrt.write_positions(particles, "pos_{}.csv".format(it + 1)) 84 | 85 | for vel in particles.Vel: 86 | E += vel.dot(vel) 87 | 88 | print("iteration {:4}/{}, N particles {}/{}, Efrac {}".format(it + 1, niter, particles.N, N, E/E0), end="\r", flush=True) 89 | 90 | 91 | print("") 92 | print("--- %s seconds ---" % (time.time() - start_time)) 93 | print('done') -------------------------------------------------------------------------------- /examples/hypersonic_flow/hypersonic_flow.py: -------------------------------------------------------------------------------- 1 | import dsmc 2 | import dsmc.writer as wrt 3 | import dsmc.diagnostics as dia 4 | import dsmc.mesh.mesh2d as msh2d 5 | import dsmc.octree as oc 6 | import time 7 | import numpy as np 8 | 9 | if __name__ == '__main__': 10 | # general parameters 11 | solver = dsmc.DSMC() 12 | domain = [(-3.0, 3.0), (-1.5, 1.5), (-0.025, 0.025)] 13 | obj = [(-0.25, 0.25), (-0.25, 0.25), (-0.5, 0.5)] 14 | dt = 1e-6 15 | w = 0.25e+15 16 | mass = 6.6422e-26 17 | T = 273.0 18 | n = 2.6e+19 19 | u = np.array([0.0, -3043.0, 0.0]) 20 | niter = 2500 21 | niter_sample = 5000 22 | 23 | # set up mesh2 24 | mesh = msh2d.Mesh2d() 25 | 26 | mesh.n_cells1 = 200 27 | mesh.n_cells2 = 100 28 | mesh.min1 = domain[0][0] 29 | mesh.min2 = domain[1][0] 30 | mesh.cell_size1 = 0.03 31 | mesh.cell_size2 = 0.03 32 | 33 | h = domain[2][1] - domain[2][0] 34 | 35 | # setup solver 36 | solver.set_domain(domain) 37 | solver.set_weight(w) 38 | solver.set_mass(mass) 39 | 40 | # set up boundary 41 | solver.set_bc_type("xmin", "inflow") 42 | solver.set_bc_type("xmax", "inflow") 43 | solver.set_bc_type("ymax", "inflow") 44 | 45 | solver.set_bc_type("ymin", "open") 46 | 47 | solver.set_bc_values("xmin", T, n, u) 48 | solver.set_bc_values("xmax", T, n, u) 49 | solver.set_bc_values("ymax", T, n, u) 50 | 51 | # set object 52 | solver.add_object(obj) 53 | 54 | # create particles 55 | solver.create_particles(domain, T, n, u) 56 | 57 | # trees 58 | tree_inner = oc.Octree() 59 | tree_outer = oc.Octree() 60 | 61 | inner_pos = np.array([[-0.25, -0.25, -0.025], [0.25, 0.25, 0.025]]) 62 | outer_pos = np.array([[-3.0, -1.5, -0.025], [3.0, 1.5, 0.025]]) 63 | 64 | tree_inner.build(inner_pos) 65 | tree_outer.build(outer_pos) 66 | 67 | wrt.write_buttom_leafs(tree_inner, "innter.vtu") 68 | wrt.write_buttom_leafs(tree_outer, "outer.vtu") 69 | 70 | # start timing 71 | start_time = time.time() 72 | 73 | for it in range(niter): 74 | print("iteration {:4}/{}".format(it + 1, niter), end="\r", flush=True) 75 | solver.advance(dt) 76 | 77 | for it in range(niter_sample): 78 | print("iteration {:4}/{}".format(it + 1, niter_sample), end="\r", flush=True) 79 | solver.advance(dt) 80 | 81 | mesh.sort(solver.particles.Pos) 82 | boxes, values = dia.analyse_2d(solver.particles.Pos, solver.particles.Vel, mesh, h) 83 | wrt.write_planar(boxes, values, "hypersonic_{}.vtu".format(it)) 84 | 85 | wrt.write_buttom_leafs(solver.octree) 86 | 87 | print("") 88 | print("--- %s seconds ---" % (time.time() - start_time)) 89 | print('done') -------------------------------------------------------------------------------- /tests/unit/test_dsmc/particles.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | from dsmc import particles as pa 3 | import numpy as np 4 | 5 | class TestParticles(unittest.TestCase): 6 | def test_box_muller(self): 7 | T = 300 8 | result = pa.box_muller(T) 9 | 10 | def test_x2velocity(self): 11 | x = 1.0 12 | mass = 1.0e-26 13 | result = pa.x2velocity(x, mass) 14 | 15 | def test_get_vel(self): 16 | T = 300 17 | mass = 1.0e-26 18 | result = pa.get_vel(T, mass) 19 | 20 | def test_get_velocities(self): 21 | T = 300 22 | mass = 1.0e-26 23 | N = 1000 24 | u = np.zeros(3) 25 | velocities = pa.get_velocities(T, mass, N, u) 26 | 27 | self.assertEqual(N, len(velocities)) 28 | 29 | def test_calc_temperature(self): 30 | T = 300 31 | mass = 1.0e-26 32 | N = 10000 33 | u = np.zeros(3) 34 | velocities = pa.get_velocities(T, mass, N, u) 35 | T_new = pa.calc_temperature(velocities, mass) 36 | diff = abs((T_new - T)/T) 37 | 38 | self.assertTrue(diff < 0.1) 39 | 40 | def test_calc_positions(self): 41 | x = (-1.0, 1.0) 42 | y = (2.0, 3.0) 43 | z = (-2.0, -1.0) 44 | X = np.array([x, y, z]) 45 | N = 1000 46 | positions = pa.calc_positions(X, N) 47 | 48 | self.assertEqual(N, len(positions)) 49 | 50 | def test_create_particles(self): 51 | x = (-1.0, 1.0) 52 | y = (2.0, 3.0) 53 | z = (-2.0, -1.0) 54 | X = np.array((x, y, z)) 55 | N = 1000 56 | mass = 1.0e-26 57 | T = 300 58 | u = np.zeros(3) 59 | particles = pa.Particles() 60 | 61 | particles.create_particles(X, mass, T, N, u) 62 | 63 | self.assertEqual(N, len(particles.Pos)) 64 | self.assertEqual(N, len(particles.Vel)) 65 | self.assertEqual(N, particles.N) 66 | 67 | for i in range(N): 68 | self.assertTrue(particles.Pos[i][0] >= x[0] and particles.Pos[i][0] <= x[1]) 69 | self.assertTrue(particles.Pos[i][1] >= y[0] and particles.Pos[i][1] <= y[1]) 70 | self.assertTrue(particles.Pos[i][2] >= z[0] and particles.Pos[i][2] <= z[1]) 71 | 72 | particles.create_particles(X, mass, T, N, u) 73 | 74 | self.assertEqual(2*N, len(particles.Pos)) 75 | self.assertEqual(2*N, len(particles.Vel)) 76 | self.assertEqual(2*N, particles.N) 77 | 78 | for i in range(2*N): 79 | self.assertTrue(particles.Pos[i][0] >= x[0] and particles.Pos[i][0] <= x[1]) 80 | self.assertTrue(particles.Pos[i][1] >= y[0] and particles.Pos[i][1] <= y[1]) 81 | self.assertTrue(particles.Pos[i][2] >= z[0] and particles.Pos[i][2] <= z[1]) 82 | 83 | def test_calc_vp(self): 84 | T = 300 85 | mass = 1e-26 86 | vp = pa.calc_vp(T, mass) 87 | 88 | self.assertEqual(np.sqrt(2.0*pa.kb*T/mass), vp) 89 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Octree based DSMC - Python implementation 2 | [![LeoBasov](https://circleci.com/gh/LeoBasov/dsmc-python.svg?style=svg)](https://app.circleci.com/pipelines/github/LeoBasov/dsmc-python/) 3 | 4 | 5 | # Table of Contents 6 | 1. Introduction 7 | 2. Requirements 8 | 3. Installation 9 | 4. Test Cases 10 | 11 | # 1. Introduction 12 | DSMC implementation using an octree as a variable mesh based on https://doi.org/10.1016/j.jcp.2008.04.038. 13 | Implementation in done in python 3.10. 14 | 15 | # 2. Requirements 16 | - python 3.10. 17 | - pip3 18 | - numpy 19 | - llvmlite 20 | - scipy 21 | - numba 22 | 23 | # 3. Installation 24 | The module can be installed using pip3 from the repository root as 25 | 26 | `` 27 | pip3 install . 28 | `` 29 | 30 | # 4. Test Cases 31 | All test cases were performed using Argon. 32 | The gas properties are as follows: 33 | 34 | | gas | $\sigma_T / m^2$ | $m / kg$ | 35 | |:---:|:----------------:|:----------:| 36 | | Ar | 3.631681e-19 | 6.6422e-26 | 37 | 38 | ## 4.1 Heat Bath 39 | Simulation of temperature relaxation of Argon in closed domain. 40 | The simulation domain is cube with a side length of $2 \cdot 10^{-3} m$. 41 | The simulation properties are as follows 42 | 43 | 44 | | $\Delta t / s$ | $w$ | $T / K$ | $n / m^{-3}$ | $u / (m/s)$ | 45 | |:--------------:|:------:|:-------:|:------------:|:-----------:| 46 | | 1e-5 | 0.5e-8 | 300 | 1e+20 | 1000.0 | 47 | 48 | where $\Delta t$ is the time step, $w$ is the particle weight, $T$ the temperature, $n$ the number density and $u$ the velocity in x direction. 49 | The simulation results can be seen below. 50 | 51 | ![Heat Bath](./examples/heat_bath/heat_bath.png) 52 | 53 | ## 4.2 Hypersonic flow around cube 54 | Hypersonic flow around a cuboid. 55 | The parameters are as follows 56 | 57 | | $\Delta t / s$ | $w$ | $T / K$ | $n / m^{-3}$ | $v_{x, z} / (m s^{-1})$ | $v_y / (m s^{-1})$ | 58 | |:--------------:|:--------:|:-------:|:------------:|:-----------------------:|:------------------:| 59 | | 1e-6 | 0.25e+15 | 273.0 | 2.6e+19 | 0 | -3043.0 | 60 | 61 | ![hypersonic_flow](./examples/hypersonic_flow/hypersonic_flow.png) 62 | 63 | ![hypersonic_flow_grid](./examples/hypersonic_flow/hypersonic_flow_grid.png) 64 | 65 | ![hypersonic_flow_grid_nrho](./examples/hypersonic_flow/hypersonic_flow_grid_nrho.png) 66 | 67 | ## 4.3 Shock Tube 68 | 69 | This test case is Sod's shock tube problem. 70 | Initial conditions for the left hand side $C_L$ and the right hand side $C_R$ are found below 71 | 72 | $$ 73 | C_L = 74 | \begin{pmatrix} 75 | n_L \\ 76 | u_L \\ 77 | T_L \\ 78 | \end{pmatrix} = 79 | \begin{pmatrix} 80 | 2.41432e22 \\ 81 | 0 \\ 82 | 300 \\ 83 | \end{pmatrix} 84 | $$ 85 | 86 | $$ 87 | C_R = 88 | \begin{pmatrix} 89 | n_R \\ 90 | u_R \\ 91 | p_L \\ 92 | \end{pmatrix}= 93 | \begin{pmatrix} 94 | 2.41432e21 \\ 95 | 0 \\ 96 | 300 \\ 97 | \end{pmatrix} 98 | $$ 99 | 100 | The simulation parameters 101 | 102 | | $\Delta t / s$ | $w$ | 103 | |:--------------:|:----:| 104 | | 1e-7 | 1e-8 | 105 | 106 | The simulation domain is a rectangular tube with a square cross section with the side length $2 \cdot 10^{-4} m$ and a length of $0.1 m$. 107 | Results can be seen below. 108 | 109 | ![shock Tube](./examples/shock_tube/shock_tube.png) 110 | -------------------------------------------------------------------------------- /dsmc/mesh/mesh2d.py: -------------------------------------------------------------------------------- 1 | from enum import Enum 2 | import math 3 | from numba import njit 4 | import numpy as np 5 | 6 | @njit 7 | def _get_cell_id(val1, val2, n_cells1, n_cells2, min1, min2, cell_size1, cell_size2): 8 | if (val1 < min1): 9 | return (False, 0) 10 | elif (val1 > (min1 + n_cells1 * cell_size1)): 11 | return (False, 0) 12 | else: 13 | cell_id1 = math.floor((val1 - min1) / cell_size1) 14 | 15 | if (val2 < min2): 16 | return (False, 0) 17 | elif (val2 > (min2 + n_cells2 * cell_size2)): 18 | return (False, 0) 19 | else: 20 | cell_id2 = math.floor((val2 - min2) / cell_size2) 21 | 22 | return (True, cell_id2 * n_cells1 + cell_id1) 23 | 24 | @njit 25 | def _sort(values1, values2, n_cells1, n_cells2, min1, min2, cell_size1, cell_size2): 26 | inside = np.empty((len(values1)), np.bool_) 27 | ids = np.empty((len(values1)), np.int_) 28 | 29 | for i in range(len(values1)): 30 | inside[i], ids[i] = _get_cell_id(values1[i], values2[i], n_cells1, n_cells2, min1, min2, cell_size1, cell_size2) 31 | 32 | return (inside, ids) 33 | 34 | 35 | class Plane(Enum): 36 | XY = 0 37 | YZ = 1 38 | XZ = 2 39 | 40 | class Mesh2d: 41 | def __init__(self): 42 | self.clear() 43 | 44 | def clear(self): 45 | self.cell_size1 = 1.0 46 | self.cell_size2 = 1.0 47 | self.min1 = 0.0 48 | self.min2 = 0.0 49 | self.n_cells1 = 1 50 | self.n_cells2 = 1 51 | self.plane = Plane.XY 52 | self.cells = None # this holds an 2d array, cells[] : cells, cells[][] position ids in cell 53 | 54 | def sort(self, position): 55 | self.cells = [[] for _ in range(self.n_cells1 * self.n_cells2)] 56 | 57 | match self.plane: 58 | case Plane.XY: 59 | positions1 = np.array([position[i][0] for i in range(len(position))]) 60 | positions2 = np.array([position[i][1] for i in range(len(position))]) 61 | case Plane.YZ: 62 | positions1 = np.array([position[i][1] for i in range(len(position))]) 63 | positions2 = np.array([position[i][2] for i in range(len(position))]) 64 | case Plane.XZ: 65 | positions1 = np.array([position[i][0] for i in range(len(position))]) 66 | positions2 = np.array([position[i][2] for i in range(len(position))]) 67 | 68 | inside, cell_ids = _sort(positions1, positions2, self.n_cells1, self.n_cells2, self.min1, self.min2, self.cell_size1, self.cell_size2) 69 | sorted_ids = np.argsort(cell_ids) 70 | 71 | for idx in sorted_ids: 72 | if inside[idx]: 73 | self.cells[cell_ids[idx]].append(idx) 74 | 75 | def get_cell_id(self, position): 76 | match self.plane: 77 | case Plane.XY: 78 | return _get_cell_id(position[0], position[1], self.n_cells1, self.n_cells2, self.min1, self.min2, self.cell_size1, self.cell_size2) 79 | case Plane.YZ: 80 | return _get_cell_id(position[1], position[2], self.n_cells1, self.n_cells2, self.min1, self.min2, self.cell_size1, self.cell_size2) 81 | case Plane.XZ: 82 | return _get_cell_id(position[0], position[2], self.n_cells1, self.n_cells2, self.min1, self.min2, self.cell_size1, self.cell_size2) -------------------------------------------------------------------------------- /dsmc/writer/octree.py: -------------------------------------------------------------------------------- 1 | def write_buttom_leafs(octree, file_name="octree.vtu"): 2 | f = open(file_name, "w") 3 | 4 | _write_header(f) 5 | _wrtie_body(f, octree) 6 | _write_footer(f) 7 | 8 | f.close() 9 | 10 | def _write_header(f): 11 | f.write("\n") 12 | 13 | def _wrtie_body(f, octree): 14 | leaf_ids = [] 15 | for i in range(len(octree.leafs)): 16 | if octree.leafs[i].number_children == 0: 17 | leaf_ids.append(i) 18 | 19 | f.write("\n") 20 | f.write("\n".format(len(leaf_ids) * 8, len(leaf_ids))) 21 | 22 | _write_points(f, octree, leaf_ids) 23 | _write_cells(f, octree, leaf_ids) 24 | _write_cell_data(f, octree, leaf_ids) 25 | 26 | f.write("\n") 27 | f.write("\n") 28 | 29 | def _write_points(f, octree, leaf_ids): 30 | f.write("\n") 31 | f.write("\n") 32 | 33 | for i in leaf_ids: 34 | box = octree.cell_boxes[i] 35 | 36 | f.write("{} ".format(box[0][0])) 37 | f.write("{} ".format(box[1][0])) 38 | f.write("{} ".format(box[2][0])) 39 | 40 | f.write("{} ".format(box[0][1])) 41 | f.write("{} ".format(box[1][0])) 42 | f.write("{} ".format(box[2][0])) 43 | 44 | f.write("{} ".format(box[0][1])) 45 | f.write("{} ".format(box[1][1])) 46 | f.write("{} ".format(box[2][0])) 47 | 48 | f.write("{} ".format(box[0][0])) 49 | f.write("{} ".format(box[1][1])) 50 | f.write("{} ".format(box[2][0])) 51 | 52 | f.write("{} ".format(box[0][0])) 53 | f.write("{} ".format(box[1][0])) 54 | f.write("{} ".format(box[2][1])) 55 | 56 | f.write("{} ".format(box[0][1])) 57 | f.write("{} ".format(box[1][0])) 58 | f.write("{} ".format(box[2][1])) 59 | 60 | f.write("{} ".format(box[0][1])) 61 | f.write("{} ".format(box[1][1])) 62 | f.write("{} ".format(box[2][1])) 63 | 64 | f.write("{} ".format(box[0][0])) 65 | f.write("{} ".format(box[1][1])) 66 | f.write("{} ".format(box[2][1])) 67 | 68 | f.write("\n") 69 | f.write("\n") 70 | 71 | 72 | def _write_cells(f, octree, leaf_ids): 73 | k = 0 74 | 75 | f.write("\n") 76 | f.write("\n") 77 | 78 | for i in range(len(leaf_ids)): 79 | for _ in range(8): 80 | f.write("{} ".format(k)) 81 | k += 1 82 | 83 | f.write("\n") 84 | f.write("\n") 85 | 86 | for i in range(len(leaf_ids)): 87 | f.write("{} ".format((i + 1) * 8)) 88 | 89 | f.write("\n") 90 | f.write("\n") 91 | 92 | for _ in range(len(leaf_ids)): 93 | f.write("12 ") 94 | 95 | f.write("\n") 96 | f.write("\n") 97 | 98 | def _write_cell_data(f, octree, leaf_ids): 99 | f.write("\n") 100 | f.write("\n") 101 | 102 | for i in leaf_ids: 103 | f.write("{} ".format(octree.leafs[i].number_elements)) 104 | 105 | f.write("\n") 106 | f.write("\n") 107 | 108 | def _write_footer(f): 109 | f.write("\n") 110 | -------------------------------------------------------------------------------- /doc/Boundary.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "id": "d49edbe1-fe92-4a67-82e9-78a877139d5d", 7 | "metadata": {}, 8 | "outputs": [], 9 | "source": [ 10 | "import numpy as np\n", 11 | "import sympy as sym" 12 | ] 13 | }, 14 | { 15 | "cell_type": "markdown", 16 | "id": "7f598afc-282c-4bb5-8d47-80c77fcc1178", 17 | "metadata": {}, 18 | "source": [ 19 | "**Boundary collision method**\n", 20 | "\n", 21 | "Given a plane $\\Pi$ and and a line $L$ as\n", 22 | "\n", 23 | "$$\n", 24 | "\\Pi \\rightarrow (p - p_0) \\cdot \\vec{n}_p = 0 \\\\\n", 25 | "L \\rightarrow l = l_0 + t \\cdot \\vec{n}_l\n", 26 | "$$\n", 27 | "\n", 28 | "where $\\vec{n}_1$ is the normal vector of a plane given as\n", 29 | "\n", 30 | "$$\n", 31 | "\\vec{n}_p = (p_1 - p_0) \\times (p_2 - p_0)\n", 32 | "$$\n", 33 | "\n", 34 | "is a vector in the direction of the line as\n", 35 | "\n", 36 | "$$\n", 37 | "\\vec{n}_l = l_1 - l_0.\n", 38 | "$$\n", 39 | "\n", 40 | "The positons of the intersection point found by setting the point $p$ in the equation for the plane as being a point in the equation of the line:\n", 41 | "\n", 42 | "$$\n", 43 | "(l - p_0) \\cdot \\vec{n}_p = 0 = (l_0 + t \\cdot \\vec{n}_l - p_0) \\cdot \\vec{n}_p \\implies t = - \\frac{(l_0 - p_0) \\cdot \\vec{n}_p}{\\vec{n}_p \\cdot \\vec{n}_l}\n", 44 | "$$\n", 45 | "\n", 46 | "inserting the line equation the intersection point can be found as\n", 47 | "\n", 48 | "$$\n", 49 | "l^* = l_0 + t \\cdot \\vec{n}_l.\n", 50 | "$$" 51 | ] 52 | }, 53 | { 54 | "cell_type": "code", 55 | "execution_count": 2, 56 | "id": "4abb0e41-5e15-4326-b663-df0b6b5cfe0b", 57 | "metadata": { 58 | "tags": [] 59 | }, 60 | "outputs": [ 61 | { 62 | "name": "stdout", 63 | "output_type": "stream", 64 | "text": [ 65 | "[0. 0. 0.]\n" 66 | ] 67 | } 68 | ], 69 | "source": [ 70 | "l1 = np.array([1.0, 1.0, 0.0])\n", 71 | "l0 = np.array([-1.0, -1.0, 0.0])\n", 72 | "\n", 73 | "p0 = np.array([0.0, -1.0, -1.0])\n", 74 | "p1 = np.array([0.0, -1.0, 1.0])\n", 75 | "p2 = np.array([0.0, 1.0, 1.0])\n", 76 | "\n", 77 | "nl = l1 - l0\n", 78 | "n_p = np.cross((p1 - p0), (p2 - p0))\n", 79 | "\n", 80 | "t = - ((l0 - p0).dot(n_p) / n_p.dot(nl))\n", 81 | "\n", 82 | "ls = l0 +t*nl\n", 83 | "\n", 84 | "print(ls)" 85 | ] 86 | }, 87 | { 88 | "cell_type": "markdown", 89 | "id": "d43f6e71-7324-4b21-9c0d-371fb76d01f6", 90 | "metadata": {}, 91 | "source": [ 92 | "**Reflections**\n", 93 | "\n", 94 | "The reflected line can be found as\n", 95 | "\n", 96 | "$$\n", 97 | "L_R \\rightarrow l_R = l^* + \\lambda \\cdot \\vec{n}_R\n", 98 | "$$\n", 99 | "\n", 100 | "with \n", 101 | "\n", 102 | "$$\n", 103 | "\\vec{n}_R = \\vec{n}_l - 2 \\frac{\\vec{n}_p \\cdot \\vec{n}_l}{|| \\vec{n}_p ||^2} \\cdot \\vec{n}_p.\n", 104 | "$$\n", 105 | "\n", 106 | "The reflected point can now the found as \n", 107 | "\n", 108 | "$$\n", 109 | "l_R = l^* + (1 - t) \\cdot \\vec{n}_R\n", 110 | "$$" 111 | ] 112 | }, 113 | { 114 | "cell_type": "code", 115 | "execution_count": 3, 116 | "id": "91de06b7-7511-471d-9b64-f9c2a784d682", 117 | "metadata": {}, 118 | "outputs": [ 119 | { 120 | "data": { 121 | "text/plain": [ 122 | "array([ 1., -1., 0.])" 123 | ] 124 | }, 125 | "execution_count": 3, 126 | "metadata": {}, 127 | "output_type": "execute_result" 128 | } 129 | ], 130 | "source": [ 131 | "nR = nl - 2*(n_p.dot(nl) / n_p.dot(n_p))*n_p\n", 132 | "lR = ls - (1 -t )*nR\n", 133 | "\n", 134 | "lR" 135 | ] 136 | }, 137 | { 138 | "cell_type": "code", 139 | "execution_count": null, 140 | "id": "a81e9e3a-d8d0-463f-a5e4-b8700e696875", 141 | "metadata": {}, 142 | "outputs": [], 143 | "source": [] 144 | } 145 | ], 146 | "metadata": { 147 | "kernelspec": { 148 | "display_name": "Python 3 (ipykernel)", 149 | "language": "python", 150 | "name": "python3" 151 | }, 152 | "language_info": { 153 | "codemirror_mode": { 154 | "name": "ipython", 155 | "version": 3 156 | }, 157 | "file_extension": ".py", 158 | "mimetype": "text/x-python", 159 | "name": "python", 160 | "nbconvert_exporter": "python", 161 | "pygments_lexer": "ipython3", 162 | "version": "3.8.10" 163 | } 164 | }, 165 | "nbformat": 4, 166 | "nbformat_minor": 5 167 | } 168 | -------------------------------------------------------------------------------- /dsmc/particles.py: -------------------------------------------------------------------------------- 1 | import math 2 | import numpy as np 3 | from numba import njit 4 | import numba 5 | from . import common as com 6 | 7 | kb = 1.380649e-23 8 | 9 | @njit(numba.float64(numba.float64, numba.float64)) 10 | def calc_vp(T, mass): 11 | return np.sqrt(2*kb*T/mass) 12 | 13 | @njit(numba.float64(numba.float64)) 14 | def box_muller(T): 15 | """ 16 | Parameters 17 | ---------- 18 | T : float 19 | temperature [K] 20 | 21 | Returns 22 | ------- 23 | x : float 24 | m * v^2 / (2 * kb) 25 | """ 26 | r1 = np.random.random() 27 | r2 = np.random.random() 28 | r3 = np.random.random() 29 | 30 | return T*(-np.log(r1) - np.log(r2) * math.pow(np.cos((np.pi/2.0)*r3), 2)) 31 | 32 | @njit(numba.float64(numba.float64, numba.float64)) 33 | def x2velocity(x, mass): 34 | """ 35 | Parameters 36 | ---------- 37 | x : float 38 | m * v^2 / (2 * kb) 39 | mass : float 40 | particle mass [kg] 41 | 42 | Returns 43 | ------- 44 | speed of particle : float 45 | """ 46 | return math.sqrt(2.0 * x * kb /mass) 47 | 48 | @njit(numba.float64[:](numba.float64, numba.float64)) 49 | def get_vel(T, mass): 50 | """ 51 | Parameters 52 | ---------- 53 | T : float 54 | temperature [K] 55 | mass : float 56 | particle mass [kg] 57 | 58 | Returns 59 | ------- 60 | velocity : np.array, shape = (3, 1) 61 | """ 62 | v = np.random.random(3)*2.0 - np.ones(3) 63 | return v * x2velocity(box_muller(T), mass) / np.linalg.norm(v) 64 | 65 | @njit(numba.float64[:, :](numba.float64, numba.float64, numba.int64, numba.float64[:])) 66 | def get_velocities(T, mass, N, u): 67 | velocities = np.empty((N, 3)) 68 | 69 | for i in range(N): 70 | velocities[i] = get_vel(T, mass) + u 71 | 72 | return velocities 73 | 74 | @njit 75 | def calc_temperature(velocities, mass): 76 | tot_e = 0.0 77 | 78 | if not len(velocities): 79 | return 0.0 80 | 81 | for i in range(len(velocities)): 82 | tot_e += 0.5 * mass * np.dot(velocities[i], velocities[i]) 83 | 84 | return tot_e / ((3.0/2.0) * len(velocities) * kb) 85 | 86 | @njit(numba.float64[:, :](numba.float64[:, :], numba.int64)) 87 | def calc_positions(X, N): 88 | """ 89 | Parameters 90 | ---------- 91 | x : tuple(2), dtype = float 92 | xmin, xmax 93 | y : tuple(2), dtype = float 94 | ymin, ymax 95 | z : tuple(2), dtype = float 96 | zmin, zmax 97 | """ 98 | positions = np.empty((N, 3)) 99 | 100 | for i in range(N): 101 | for j in range(3): 102 | positions[i][j] = X[j][0] + np.random.random() * (X[j][1] - X[j][0]) 103 | 104 | return positions 105 | 106 | class Particles: 107 | def __init__(self): 108 | self._velocities = None 109 | self._positions = None 110 | self._N = 0 # number of particles 111 | 112 | @property 113 | def Vel(self): 114 | return self._velocities 115 | 116 | @property 117 | def Pos(self): 118 | return self._positions 119 | 120 | @property 121 | def N(self): 122 | return self._N 123 | 124 | @property 125 | def VelPos(self): 126 | return (self._velocities, self._positions) 127 | 128 | @VelPos.setter 129 | def VelPos(self, vel_pos): 130 | assert len(vel_pos[0]) == len(vel_pos[1]) 131 | 132 | self._velocities = vel_pos[0] 133 | self._positions = vel_pos[1] 134 | self._N = len(self._positions) 135 | 136 | def create_particles(self, X, mass, T, N, u = np.zeros(3)): 137 | if self._N == 0: 138 | self._velocities = get_velocities(T, mass, N, u) 139 | self._positions = calc_positions(X, N) 140 | self._N = N 141 | else: 142 | self._velocities = np.concatenate((self._velocities, get_velocities(T, mass, N, u))) 143 | self._positions = np.concatenate((self._positions, calc_positions(X, N))) 144 | self._N += N 145 | 146 | 147 | def inflow(self, mass, T, u, n, w, dt, domain, axis, minmax): 148 | L = max(calc_vp(T, mass) * dt * 10, np.linalg.norm(u) * dt) 149 | box = np.copy(domain) 150 | 151 | if minmax == 0: 152 | box[axis][1] = box[axis][0] 153 | box[axis][0] = box[axis][1] - L 154 | elif minmax == 1: 155 | box[axis][0] = box[axis][1] 156 | box[axis][1] = box[axis][0] + L 157 | 158 | N = int(round(com.get_V(box) * n / w)) 159 | 160 | self.create_particles(box, mass, T, N, u) 161 | -------------------------------------------------------------------------------- /examples/shock_tube/tools/sod_analytical.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Thu Sep 29 12:03:03 2022 4 | 5 | @author: Leo Basov 6 | """ 7 | 8 | import numpy as np 9 | import matplotlib.pyplot as plt 10 | import argparse 11 | 12 | kb = 1.380649e-23 13 | 14 | def _calc_u3(p1, p3, rhoL, Gamma, gamma, beta): 15 | num = (1 - Gamma**2) * p1**(1.0/gamma) 16 | denum = Gamma**2 * rhoL 17 | return (p1**beta - p3**beta) * np.sqrt(num / denum) 18 | 19 | def _calc_u4(p3, p5, rhoR, Gamma): 20 | return (p3 - p5) * np.sqrt((1 - Gamma) / (rhoR*(p3 - Gamma*p5))) 21 | 22 | def _calc_p3(p, rho, Gamma, gamma, beta): 23 | p1 = p[0] 24 | p3 = p[0] 25 | p5 = p[4] 26 | dp = p1 * 1e-3 27 | rhoL = rho[0] 28 | rhoR = rho[-1] 29 | err = 1e+5 30 | err_last = 1e+6 31 | 32 | while err < err_last: 33 | err_last = err 34 | err = abs(_calc_u3(p1, p3, rhoL, Gamma, gamma, beta) - _calc_u4(p3, p5, rhoR, Gamma)) 35 | p3 -= dp 36 | 37 | return p3 38 | 39 | def plot_val(x, val, name): 40 | plt.plot((x[0], x[1]), (val[0], val[1])) 41 | plt.plot((x[1], x[2]), (val[1], val[2])) 42 | plt.plot((x[2], x[3]), (val[2], val[2])) 43 | plt.plot((x[3], x[3]), (val[2], val[3])) 44 | plt.plot((x[3], x[4]), (val[3], val[3])) 45 | plt.plot((x[4], x[4]), (val[3], val[4])) 46 | plt.plot((x[4], x[5]), (val[4], val[4])) 47 | 48 | plt.ylabel(name) 49 | plt.xlabel("x") 50 | 51 | plt.show() 52 | 53 | def write_values(x, val, name, file): 54 | with open(file + "_" + name + ".csv", "w") as file: 55 | file.write("{}, {}\n".format(x[0], val[0])) 56 | file.write("{}, {}\n".format(x[1], val[1])) 57 | file.write("{}, {}\n".format(x[2], val[2])) 58 | file.write("{}, {}\n".format(x[3], val[2])) 59 | file.write("{}, {}\n".format(x[3], val[3])) 60 | file.write("{}, {}\n".format(x[4], val[3])) 61 | file.write("{}, {}\n".format(x[4], val[4])) 62 | file.write("{}, {}\n".format(x[5], val[4])) 63 | 64 | def check_args(args): 65 | if args.p is not None and (args.p[0] <= args.p[1]): 66 | raise Exception("p1 must be > p2") 67 | elif args.rho is not None and (args.rho[0] <= args.rho[1]): 68 | raise Exception("rho1 must be > rho2") 69 | elif args.L is not None and (args.L <= 0.0): 70 | raise Exception("L must be > 0") 71 | 72 | if __name__ == '__main__': 73 | parser = argparse.ArgumentParser() 74 | parser.add_argument('-t', type=float, help='time of results', default=3.0e-5) 75 | parser.add_argument('-p', type=float, help='pressure', nargs = 2, default=(100, 10.0)) 76 | parser.add_argument('-rho', type=float, help='density', nargs = 2, default=(0.0016036396304, 0.0016036396304*0.1)) 77 | parser.add_argument('-L', type=float, help='tube length', default=0.1) 78 | parser.add_argument('-plt', type=bool, help='plot values', const=True, nargs='?') 79 | parser.add_argument('-w', type=str, help='write to file') 80 | 81 | args = parser.parse_args() 82 | 83 | check_args(args) 84 | 85 | # number points per segment 86 | N = 10 87 | 88 | # gas = Ar 89 | gamma = 1.67 90 | Gamma = (gamma - 1.0) / (gamma + 1.0) 91 | beta = (gamma - 1.0) / (2.0 * gamma) 92 | mass = 6.6422e-26 93 | 94 | # boundary conditions 95 | rho = np.zeros(5) 96 | p = np.zeros(5) 97 | u = np.zeros(5) 98 | 99 | rho[0] = args.rho[0] 100 | p[0] = args.p[0] 101 | u[0] = 0.0 102 | 103 | rho[-1] = args.rho[1] 104 | p[-1] = args.p[1] 105 | u[-1] = 0.0 106 | 107 | # calculating states 108 | p[1] = p[0] 109 | p[2] = _calc_p3(p, rho, Gamma, gamma, beta) 110 | p[3] = p[2] 111 | 112 | # speed of characterisics 113 | u[1] = np.sqrt(gamma * p[0] / rho[0]) # speed of rarefication going left 114 | u[2] = 0 115 | u[3] = (p[2] - p[4]) / np.sqrt((rho[4]/2) * ((gamma + 1) * p[2] + (gamma - 1) * p[4])) 116 | u[4] = np.sqrt(gamma * p[-1] / rho[-1]) # speed of pressure increase going right 117 | 118 | rho[1] = rho[0] 119 | rho[2] = rho[0]*(p[2] / p[0])**(1.0/gamma) 120 | rho[3] = rho[4] * (p[3] + Gamma*p[4]) / (p[4] + Gamma*p[3]) 121 | 122 | n = [r/mass for r in rho] 123 | T = [p[i] / (n[i] * kb) for i in range(5)] 124 | 125 | # calc x 126 | x = np.array([0.0, args.L*0.5 - args.t*u[1], args.L*0.5, args.L*0.5 + args.t*u[3], args.L*0.5 + args.t*u[3] + args.t*u[4], args.L]) 127 | 128 | if args.plt: 129 | plot_val(x, rho, "rho") 130 | plot_val(x, n, "n") 131 | plot_val(x, p, "p") 132 | plot_val(x, T, "T") 133 | 134 | if args.w: 135 | print("writing to file " + args.w + "_X.csv") 136 | write_values(x, rho, "rho", args.w) 137 | write_values(x, p, "p", args.w) 138 | write_values(x, n, "n", args.w) 139 | write_values(x, T, "T", args.w) 140 | 141 | print("done") 142 | -------------------------------------------------------------------------------- /tests/unit/test_dsmc/mesh/mesh2d.py: -------------------------------------------------------------------------------- 1 | import dsmc.mesh.mesh2d as msh 2 | import unittest 3 | import numpy as np 4 | 5 | class TestMesh2(unittest.TestCase): 6 | def test_constructor(self): 7 | mesh = msh.Mesh2d() 8 | 9 | self.assertEqual(1.0, mesh.cell_size1) 10 | self.assertEqual(1.0, mesh.cell_size2) 11 | self.assertEqual(0.0, mesh.min1) 12 | self.assertEqual(0.0, mesh.min2) 13 | self.assertEqual(1, mesh.n_cells1) 14 | self.assertEqual(1, mesh.n_cells2) 15 | self.assertEqual(msh.Plane.XY, mesh.plane) 16 | 17 | def test__get_cell_id1(self): 18 | val1_f = -1.0 19 | val1_t = 0.1 20 | val2_f = -1.0 21 | val2_t = 0.1 22 | n_cells1 = 10 23 | n_cells2 = 10 24 | min1 = -0.5 25 | min2 = -0.5 26 | cell_size1 = 0.1 27 | cell_size2 = 0.1 28 | 29 | res1_f = msh._get_cell_id(val1_t, val2_f, n_cells1, n_cells2, min1, min2, cell_size1, cell_size2) 30 | res2_f = msh._get_cell_id(val1_f, val2_t, n_cells1, n_cells2, min1, min2, cell_size1, cell_size2) 31 | res3_t = msh._get_cell_id(val1_t, val2_t, n_cells1, n_cells2, min1, min2, cell_size1, cell_size2) 32 | 33 | self.assertFalse(res1_f[0]) 34 | self.assertFalse(res2_f[0]) 35 | self.assertTrue(res3_t[0]) 36 | 37 | def test__get_cell_id2(self): 38 | val1 = (-0.45, -0.5) 39 | val2 = (-0.35, -0.35) 40 | n_cells1 = 10 41 | n_cells2 = 10 42 | min1 = -0.5 43 | min2 = -0.5 44 | cell_size1 = 0.1 45 | cell_size2 = 0.1 46 | 47 | res1 = msh._get_cell_id(val1[0], val1[1], n_cells1, n_cells2, min1, min2, cell_size1, cell_size2) 48 | res2 = msh._get_cell_id(val2[0], val2[1], n_cells1, n_cells2, min1, min2, cell_size1, cell_size2) 49 | 50 | self.assertTrue(res1[0]) 51 | self.assertTrue(res2[0]) 52 | 53 | self.assertEqual(0, res1[1]) 54 | self.assertEqual(11, res2[1]) 55 | 56 | def test_get_cell_id(self): 57 | mesh = msh.Mesh2d() 58 | 59 | mesh.n_cells1 = 10 60 | mesh.n_cells2 = 10 61 | mesh.min1 = -0.5 62 | mesh.min2 = -0.5 63 | mesh.cell_size1 = 0.1 64 | mesh.cell_size2 = 0.1 65 | 66 | pos = np.array([-0.45, -0.35, -0.25]) 67 | 68 | # XY 69 | mesh.plane = msh.Plane.XY 70 | res = mesh.get_cell_id(pos) 71 | 72 | self.assertTrue(res[0]) 73 | self.assertEqual(10, res[1]) 74 | 75 | # YZ 76 | mesh.plane = msh.Plane.YZ 77 | res = mesh.get_cell_id(pos) 78 | 79 | self.assertTrue(res[0]) 80 | self.assertEqual(21, res[1]) 81 | 82 | # XZ 83 | mesh.plane = msh.Plane.XZ 84 | res = mesh.get_cell_id(pos) 85 | 86 | self.assertTrue(res[0]) 87 | self.assertEqual(20, res[1]) 88 | 89 | def test__sort(self): 90 | mesh = msh.Mesh2d() 91 | 92 | mesh.n_cells1 = 10 93 | mesh.n_cells2 = 10 94 | mesh.min1 = -0.5 95 | mesh.min2 = -0.5 96 | mesh.cell_size1 = 0.1 97 | mesh.cell_size2 = 0.1 98 | 99 | pos1 = np.array([-0.45, -0.35, 0.0]) 100 | pos2 = np.array([-0.45, -3.50, 0.0]) 101 | positions = np.array([pos1, pos2]) 102 | 103 | values1 = np.array([positions[i][0] for i in range(len(positions))]) 104 | values2 = np.array([positions[i][1] for i in range(len(positions))]) 105 | 106 | inside, ids = msh._sort(values1, values2, mesh.n_cells1, mesh.n_cells2, mesh.min1, mesh.min2, mesh.cell_size1, mesh.cell_size2) 107 | 108 | self.assertTrue(inside[0]) 109 | self.assertFalse(inside[1]) 110 | 111 | self.assertEqual(10, ids[0]) 112 | self.assertEqual(0, ids[1]) 113 | 114 | def test_sort(self): 115 | mesh = msh.Mesh2d() 116 | 117 | mesh.n_cells1 = 10 118 | mesh.n_cells2 = 10 119 | mesh.min1 = -0.5 120 | mesh.min2 = -0.5 121 | mesh.cell_size1 = 0.1 122 | mesh.cell_size2 = 0.1 123 | 124 | positions = [] 125 | 126 | positions.append([-0.45, -0.45, 0]) 127 | positions.append([-0.45, -0.45, 0]) 128 | 129 | positions.append([0.45, 0.45, 0]) 130 | 131 | mesh.sort(positions) 132 | 133 | self.assertEqual(len(mesh.cells), mesh.n_cells1 * mesh.n_cells2) 134 | self.assertEqual(len(mesh.cells[0]), 2) 135 | self.assertEqual(len(mesh.cells[99]), 1) 136 | 137 | self.assertEqual(mesh.cells[0][0], 0) 138 | self.assertEqual(mesh.cells[0][1], 1) 139 | self.assertEqual(mesh.cells[99][0], 2) 140 | 141 | for i in range(len(mesh.cells)): 142 | if i != 0 and i != 99: 143 | self.assertEqual(0, len(mesh.cells[i])) -------------------------------------------------------------------------------- /tests/unit/test_data/particles.csv: -------------------------------------------------------------------------------- 1 | 0.16720244270111206,0.8208120902385547,-0.15821775757746326 2 | -0.3539408610094026,0.6094479586781756,-0.2241998042084452 3 | -0.253602773408937,0.37842838770619047,0.5080805107290469 4 | 0.901801119661219,-0.3547753241315563,-0.7994223817818384 5 | -0.014540968173746727,-0.6057811852068014,-0.7747150654889452 6 | 0.6652045024170465,0.7496016129090863,0.09269932097207323 7 | -0.08371757238708022,-0.49569628427213286,-0.5230501995932113 8 | -0.45628210172061734,-0.7032547855919364,-0.01052801065881459 9 | -0.4050878274555494,0.16220023223033286,-0.13943218567361249 10 | -0.44015418512841675,0.4399168343737543,-0.13664372635262478 11 | 0.3822321359090435,-0.03867223327253977,-0.04984480804603453 12 | -0.5467265015048175,0.7694212897999899,0.5107554092663027 13 | 0.39267358552702203,0.8855795814797593,-0.3874196750436716 14 | 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-0.6040348148625538,0.4530362126423204,0.498118925527959 60 | 0.4136176171187369,-0.9050493502417782,-0.29965017480855916 61 | -0.42774070010191867,-0.06461591748042528,-0.7976491333955078 62 | 0.09766097044471311,-0.16598582888531488,-0.7608659826062489 63 | 0.33798463823175595,-0.42150973385006063,-0.3713352945819577 64 | -0.58932187049589,0.3813552375040625,-0.26284015727708554 65 | -0.4907965754459813,0.20341783229024646,0.6622776161420185 66 | 0.8098477083222237,-0.8719199252159624,0.7488605548345317 67 | -0.8193929114745129,0.840626931453603,-0.6315912117747844 68 | -0.24239201418824297,0.47098841467093844,-0.669183593651901 69 | 0.5041947220259142,-0.29544662686416756,-0.5914541788966325 70 | -0.26262096117978784,0.9801755149383851,0.527269048439474 71 | 0.4275209506977513,-0.667659249339922,0.1347518319999672 72 | 0.9855519426068913,-0.6135765984848576,-0.4287141280807911 73 | 0.20982860758802357,0.07462089616107126,0.5943311631472485 74 | 0.32596254556079907,-0.5523299607926777,0.5000136968687108 75 | 0.6298276916469507,0.7866892509990404,-0.9079439336773338 76 | 0.78142640981854,0.5399877759560965,0.6973205654874475 77 | -0.3485450193568893,-0.6303033064361121,0.17527538428193168 78 | -0.8260677718113378,0.40584791574484824,-0.9942842646615264 79 | -0.20591928046068153,-0.5923212325551002,-0.968679333547988 80 | 0.45672042754779163,0.2149643271371091,0.21071030029661353 81 | 0.057075371525048046,-0.6650594086767447,-0.5251178367633449 82 | 0.1809775156746154,0.4818178472834924,0.3972083715175747 83 | -0.6207155824174482,-0.4160776878844272,0.6917477102880314 84 | -0.904590420565192,-0.193648165470109,0.5189271677890341 85 | 0.7951185512115042,-0.6569231762630592,0.3204489978755769 86 | 0.7584068620500117,-0.3176223099304243,-0.870445024417934 87 | -0.4922227934260852,-0.5001060615332293,-0.5348416435824386 88 | 0.8605684066110679,0.16239313316117032,-0.7627141519458742 89 | 0.6590758735534021,0.9222932137960997,-0.021059658756133137 90 | -0.5501989000546204,0.26214029221325275,-0.6910176960391732 91 | 0.967198486330149,-0.41117570121974034,0.6945615910511642 92 | 0.9468060139718262,0.5879482989935261,0.08334965744250988 93 | 0.4824650338598835,-0.21178248688885692,-0.9756564237429781 94 | 0.253591146580193,0.08009088613267878,0.4274284592732791 95 | -0.4389966392317204,0.22920620294282146,-0.0002775036237094852 96 | -0.7146674493249148,-0.538980218854364,0.879679600158005 97 | 0.8244476665630003,-0.7994155142294497,-0.6359195332795282 98 | 0.6824501498828124,-0.8031118692347363,0.9876378371063732 99 | 0.718260570290431,0.3877012248400389,0.5868224029728766 100 | -0.7941746749515597,-0.49028054610731187,0.9579007583397083 101 | -------------------------------------------------------------------------------- /dsmc/boundary.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from numba import njit 3 | from . import common as co 4 | 5 | @njit(cache=True) 6 | def _check_if_parallel(v1, v2, diff=1e-6): 7 | n1 = np.linalg.norm(v1) 8 | n2 = np.linalg.norm(v2) 9 | 10 | if n1 < 1.0e-13 or n2 < 1.0e-13: 11 | return False 12 | 13 | V1 = np.copy(v1) / n1 14 | V2 = np.copy(v2) / n2 15 | 16 | return V1.dot(V2) > diff 17 | 18 | @njit(cache=True) 19 | def _intersect(l0, l1, p0, p1, p2): 20 | """ 21 | Args: 22 | l0 : first position on line 23 | l1 : second position on line 24 | p0 : first position on plane 25 | p1 : first position on plane 26 | p2 : first position on plane 27 | 28 | Returns: 29 | (intersected, n_l, n_r, t) 30 | """ 31 | n_l = l1 - l0 32 | n_p = np.cross((p1 - p0), (p2 - p1)) 33 | 34 | if _check_if_parallel(n_l, n_p): 35 | return (True, n_l, n_p, - ((l0 - p0).dot(n_p) / n_p.dot(n_l))) 36 | else: 37 | return (False, n_l, n_p, 0.0) 38 | 39 | @njit(cache=True) 40 | def _calc_nr(n_l, n_p): 41 | return n_l - 2.0 * (n_p.dot(n_l) / n_p.dot(n_p))*n_p 42 | 43 | @njit(cache=True) 44 | def _reflect(vel, pos, pos_old, p0, p1, p2, domain): 45 | intersected, n_l, n_p, t = _intersect(pos_old, pos, p0, p1, p2) 46 | 47 | if intersected and t < 1.0 and t > 0.0: 48 | k = 1.0 49 | p = pos_old + n_l*(t*k) 50 | while not co.is_inside(p, domain): 51 | k *= 0.9 52 | p = pos_old + n_l*(t*k) 53 | pos_old = p 54 | n_r = _calc_nr(n_l, n_p) 55 | pos = pos_old + (1.0 - t)*n_r 56 | vel = (np.linalg.norm(vel) / np.linalg.norm(n_r))*n_r 57 | 58 | return (vel, pos, pos_old) 59 | 60 | @njit(cache=True) 61 | def _get_plane(domain, i, j): 62 | if i == 0: 63 | if j == 0: 64 | p0 = np.array([domain[i][j], domain[1][0], domain[2][0]]) 65 | p1 = np.array([domain[i][j], domain[1][0], domain[2][1]]) 66 | p2 = np.array([domain[i][j], domain[1][1], domain[2][0]]) 67 | elif j == 1: 68 | p0 = np.array([domain[i][j], domain[1][0], domain[2][0]]) 69 | p1 = np.array([domain[i][j], domain[1][1], domain[2][0]]) 70 | p2 = np.array([domain[i][j], domain[1][0], domain[2][1]]) 71 | elif i == 1: 72 | if j == 0: 73 | p0 = np.array([domain[0][0], domain[i][j], domain[2][0]]) 74 | p1 = np.array([domain[0][1], domain[i][j], domain[2][0]]) 75 | p2 = np.array([domain[0][0], domain[i][j], domain[2][1]]) 76 | if j == 1: 77 | p0 = np.array([domain[0][0], domain[i][j], domain[2][0]]) 78 | p1 = np.array([domain[0][0], domain[i][j], domain[2][1]]) 79 | p2 = np.array([domain[0][1], domain[i][j], domain[2][0]]) 80 | elif i == 2: 81 | if j == 0: 82 | p0 = np.array([domain[0][0], domain[1][0], domain[i][j]]) 83 | p1 = np.array([domain[0][0], domain[1][1], domain[i][j]]) 84 | p2 = np.array([domain[0][1], domain[1][0], domain[i][j]]) 85 | if j == 1: 86 | p0 = np.array([domain[0][0], domain[1][0], domain[i][j]]) 87 | p1 = np.array([domain[0][1], domain[1][0], domain[i][j]]) 88 | p2 = np.array([domain[0][0], domain[1][1], domain[i][j]]) 89 | 90 | return (p0, p1, p2) 91 | 92 | @njit(cache=True) 93 | def _boundary(velocities, positions, old_positions, domain, boundary_conds): 94 | kept_parts = np.ones(positions.shape[0], dtype=np.uint) 95 | 96 | for p in range(len(positions)): 97 | counter = 0 98 | while not co.is_inside(positions[p], domain) and kept_parts[p]: 99 | if counter > 10: 100 | kept_parts[p] = 0 101 | break 102 | 103 | for i in range(3): 104 | for j in range(2): 105 | p0, p1, p2 = _get_plane(domain, i, j) 106 | if boundary_conds[i][j] == 0: 107 | velocities[p], positions[p], old_positions[p] = _reflect(velocities[p], positions[p], old_positions[p], p0, p1, p2, domain) 108 | counter += 1 109 | elif boundary_conds[i][j] == 1 or boundary_conds[i][j] == 2: 110 | if _intersect(old_positions[p], positions[p], p0, p1, p2)[0]: 111 | kept_parts[p] = 0 112 | 113 | N = int(sum(kept_parts)) 114 | p = 0 115 | new_velocities = np.empty((N, 3)) 116 | new_positions = np.empty((N, 3)) 117 | new_old_positions = np.empty((N, 3)) 118 | 119 | for i in range(positions.shape[0]): 120 | if kept_parts[i] == 1: 121 | new_velocities[p] = velocities[i] 122 | new_positions[p] = positions[i] 123 | new_old_positions[p] = old_positions[p] 124 | p += 1 125 | else: 126 | continue 127 | 128 | return (new_velocities, new_positions, new_old_positions) 129 | 130 | @njit(cache=True) 131 | def _get_boundary(boundary): 132 | if boundary == "xmin": 133 | return (0, 0) 134 | elif boundary == "xmax": 135 | return (0, 1) 136 | elif boundary == "ymin": 137 | return (1, 0) 138 | elif boundary == "ymax": 139 | return (1, 1) 140 | elif boundary == "zmin": 141 | return (2, 0) 142 | elif boundary == "zmax": 143 | return (2, 1) 144 | 145 | @njit(cache=True) 146 | def _get_bc_type(bc_type): 147 | if bc_type == "ela": 148 | return 0 149 | elif bc_type == "open": 150 | return 1 151 | elif bc_type == "inflow": 152 | return 2 153 | 154 | class Boundary: 155 | def __init__(self): 156 | self.T = np.ones((3, 2))*300.0 157 | self.n = np.ones((3, 2))*1e+18 158 | self.u = np.zeros((3, 2, 3)) 159 | self.boundary_conds = np.array([[0, 0], [0, 0], [0, 0]], dtype=np.uint) # 0 = ela, 1 = open, 2 = inflow 160 | self.domain = None 161 | 162 | def boundary(self, velocities, positions, old_positions): 163 | return _boundary(velocities, positions, old_positions, self.domain, self.boundary_conds) 164 | 165 | def set_bc_type(self, boundary, bc_type): 166 | bound = _get_boundary(boundary) 167 | bc = _get_bc_type(bc_type) 168 | 169 | self.boundary_conds[bound[0]][bound[1]] = bc 170 | 171 | print("boundary [" + boundary + "] set to [" + bc_type + "]") 172 | 173 | def set_bc_values(self, boundary, T, n, u): 174 | i, j = _get_boundary(boundary) 175 | 176 | self.T[i][j] = T 177 | self.n[i][j] = n 178 | self.u[i][j] = u 179 | 180 | print("boundary [" + boundary + "] set to values T : {}, n : {}, u : {}".format(T, n, u)) -------------------------------------------------------------------------------- /tests/unit/test_dsmc/boundary.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import dsmc.boundary as bo 3 | import unittest 4 | 5 | class TestCommon(unittest.TestCase): 6 | def test__check_if_parallel(self): 7 | v1 = np.array([1.0, 0.0, 0.0]) 8 | v2 = np.array([1.0, 0.0, 0.0]) 9 | v3 = np.array([0.0, 1.0, 1.0]) 10 | v4 = np.array([1.0e-6, 10.0, 10.0]) 11 | 12 | self.assertTrue(bo._check_if_parallel(v1, v2)) 13 | self.assertFalse(bo._check_if_parallel(v1, v3)) 14 | self.assertFalse(bo._check_if_parallel(v1, v4)) 15 | 16 | def test__intersect(self): 17 | l0 = np.array([-1.0, -1.0, 0.0]) 18 | l1 = np.array([1.0, 1.0, 0.0]) 19 | 20 | p0 = np.array([0.0, -1.0, -1.0]) 21 | p1 = np.array([0.0, 1.0, -1.0]) 22 | p2 = np.array([0.0, -1.0, 1.0]) 23 | 24 | intersected, n_l, n_p, t = bo._intersect(l0, l1, p0, p1, p2) 25 | 26 | self.assertTrue(intersected) 27 | 28 | self.assertEqual(2.0, n_l[0]) 29 | self.assertEqual(2.0, n_l[1]) 30 | self.assertEqual(0.0, n_l[2]) 31 | 32 | self.assertEqual(4.0, n_p[0]) 33 | self.assertEqual(0.0, n_p[1]) 34 | self.assertEqual(0.0, n_p[2]) 35 | 36 | self.assertEqual(0.5, t) 37 | 38 | def test__calc_nr(self): 39 | l0 = np.array([-1.0, -1.0, 0.0]) 40 | l1 = np.array([1.0, 1.0, 0.0]) 41 | 42 | p0 = np.array([0.0, -1.0, -1.0]) 43 | p1 = np.array([0.0, -1.0, 1.0]) 44 | p2 = np.array([0.0, 1.0, 1.0]) 45 | 46 | intersected, n_l, n_p, t = bo._intersect(l0, l1, p0, p1, p2) 47 | n_r = bo._calc_nr(n_l, n_p) 48 | 49 | self.assertEqual(-2.0, n_r[0]) 50 | self.assertEqual(2.0, n_r[1]) 51 | self.assertEqual(0.0, n_r[2]) 52 | 53 | def test__reflect(self): 54 | vel = np.array([123.0, 123.0, 0.0]) 55 | pos_old = np.array([-1.0, -1.0, 0.0]) 56 | pos = np.array([1.0, 1.0, 0.0]) 57 | 58 | domain = np.array([(-2.0, 0.0), (-1.0, 1.0), (-1.0, 1.0)]) 59 | 60 | p0, p1, p2 = bo._get_plane(domain, 0, 1) 61 | 62 | new_vel, new_pos, new_pos_old = bo._reflect(vel, pos, pos_old, p0, p1, p2, domain) 63 | 64 | self.assertEqual(-123.0, new_vel[0]) 65 | self.assertEqual(123.0, new_vel[1]) 66 | self.assertEqual(0.0, new_vel[2]) 67 | 68 | self.assertEqual(-1.0, new_pos[0]) 69 | self.assertEqual(1.0, new_pos[1]) 70 | self.assertEqual(0.0, new_pos[2]) 71 | 72 | self.assertEqual(0.0, new_pos_old[0]) 73 | self.assertEqual(0.0, new_pos_old[1]) 74 | self.assertEqual(0.0, new_pos_old[2]) 75 | 76 | def test__get_plane1(self): 77 | domain = np.array([(0, 1), (2, 4), (4, 7)]) 78 | axis = 0 79 | 80 | p0, p1, p2 = bo._get_plane(domain, axis, 0) 81 | 82 | self.assertEqual((3,), p0.shape) 83 | self.assertEqual((3,), p1.shape) 84 | self.assertEqual((3,), p2.shape) 85 | 86 | self.assertEqual(0.0, p0[0]) 87 | self.assertEqual(2.0, p0[1]) 88 | self.assertEqual(4.0, p0[2]) 89 | 90 | self.assertEqual(0.0, p1[0]) 91 | self.assertEqual(2.0, p1[1]) 92 | self.assertEqual(7.0, p1[2]) 93 | 94 | self.assertEqual(0.0, p2[0]) 95 | self.assertEqual(4.0, p2[1]) 96 | self.assertEqual(4.0, p2[2]) 97 | 98 | p0, p1, p2 = bo._get_plane(domain, axis, 1) 99 | 100 | self.assertEqual((3,), p0.shape) 101 | self.assertEqual((3,), p1.shape) 102 | self.assertEqual((3,), p2.shape) 103 | 104 | self.assertEqual(1.0, p0[0]) 105 | self.assertEqual(2.0, p0[1]) 106 | self.assertEqual(4.0, p0[2]) 107 | 108 | self.assertEqual(1.0, p1[0]) 109 | self.assertEqual(4.0, p1[1]) 110 | self.assertEqual(4.0, p1[2]) 111 | 112 | self.assertEqual(1.0, p2[0]) 113 | self.assertEqual(2.0, p2[1]) 114 | self.assertEqual(7.0, p2[2]) 115 | 116 | def test__get_plane2(self): 117 | domain = np.array([(0, 1), (2, 4), (4, 7)]) 118 | axis = 1 119 | 120 | p0, p1, p2 = bo._get_plane(domain, axis, 0) 121 | 122 | self.assertEqual((3,), p0.shape) 123 | self.assertEqual((3,), p1.shape) 124 | self.assertEqual((3,), p2.shape) 125 | 126 | self.assertEqual(0.0, p0[0]) 127 | self.assertEqual(2.0, p0[1]) 128 | self.assertEqual(4.0, p0[2]) 129 | 130 | self.assertEqual(1.0, p1[0]) 131 | self.assertEqual(2.0, p1[1]) 132 | self.assertEqual(4.0, p1[2]) 133 | 134 | self.assertEqual(0.0, p2[0]) 135 | self.assertEqual(2.0, p2[1]) 136 | self.assertEqual(7.0, p2[2]) 137 | 138 | p0, p1, p2 = bo._get_plane(domain, axis, 1) 139 | 140 | self.assertEqual((3,), p0.shape) 141 | self.assertEqual((3,), p1.shape) 142 | self.assertEqual((3,), p2.shape) 143 | 144 | self.assertEqual(0.0, p0[0]) 145 | self.assertEqual(4.0, p0[1]) 146 | self.assertEqual(4.0, p0[2]) 147 | 148 | self.assertEqual(0.0, p1[0]) 149 | self.assertEqual(4.0, p1[1]) 150 | self.assertEqual(7.0, p1[2]) 151 | 152 | self.assertEqual(1.0, p2[0]) 153 | self.assertEqual(4.0, p2[1]) 154 | self.assertEqual(4.0, p2[2]) 155 | 156 | def test__get_plane3(self): 157 | domain = np.array([(0, 1), (2, 4), (4, 7)]) 158 | axis = 2 159 | 160 | p0, p1, p2 = bo._get_plane(domain, axis, 0) 161 | 162 | self.assertEqual((3,), p0.shape) 163 | self.assertEqual((3,), p1.shape) 164 | self.assertEqual((3,), p2.shape) 165 | 166 | self.assertEqual(0.0, p0[0]) 167 | self.assertEqual(2.0, p0[1]) 168 | self.assertEqual(4.0, p0[2]) 169 | 170 | self.assertEqual(0.0, p1[0]) 171 | self.assertEqual(4.0, p1[1]) 172 | self.assertEqual(4.0, p1[2]) 173 | 174 | self.assertEqual(1.0, p2[0]) 175 | self.assertEqual(2.0, p2[1]) 176 | self.assertEqual(4.0, p2[2]) 177 | 178 | p0, p1, p2 = bo._get_plane(domain, axis, 1) 179 | 180 | self.assertEqual((3,), p0.shape) 181 | self.assertEqual((3,), p1.shape) 182 | self.assertEqual((3,), p2.shape) 183 | 184 | self.assertEqual(0.0, p0[0]) 185 | self.assertEqual(2.0, p0[1]) 186 | self.assertEqual(7.0, p0[2]) 187 | 188 | self.assertEqual(1.0, p1[0]) 189 | self.assertEqual(2.0, p1[1]) 190 | self.assertEqual(7.0, p1[2]) 191 | 192 | self.assertEqual(0.0, p2[0]) 193 | self.assertEqual(4.0, p2[1]) 194 | self.assertEqual(7.0, p2[2]) 195 | -------------------------------------------------------------------------------- /dsmc/octree.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import numpy.typing as npt 3 | from numba import njit 4 | import numba 5 | from enum import Enum 6 | from . import common as com 7 | 8 | fmin = np.finfo(float).min 9 | fmax = np.finfo(float).max 10 | 11 | @njit 12 | def _find_bounding_box(positions : npt.NDArray) -> npt.NDArray: 13 | box = np.array([[fmax, fmin], [fmax, fmin], [fmax, fmin]]) 14 | 15 | for pos in positions: 16 | for i in range(3): 17 | if pos[i] < box[i][0]: 18 | box[i][0] = pos[i] 19 | if pos[i] > box[i][1]: 20 | box[i][1] = pos[i] 21 | 22 | return box 23 | 24 | @njit 25 | def _calc_N_res(w : float, sigma_T : float, n : float) -> int: 26 | """ 27 | Parameters 28 | ---------- 29 | w : float 30 | particle weight 31 | sigma_t : float 32 | total cross section [m^2] 33 | n : float 34 | number density [1/m^3] 35 | """ 36 | 37 | return int(round(np.sqrt(2.0) / (32.0 * w * sigma_T**3 * n**2))) 38 | 39 | @njit 40 | def _calc_n(box : npt.NDArray, N : float, w : float) -> float: 41 | """Calculates number density in cell 42 | 43 | Parameters 44 | ---------- 45 | box : np.array(3, 3) 46 | cell 47 | N : int 48 | number of particles in cell 49 | w : float 50 | particle weight 51 | 52 | Returns 53 | ------- 54 | number density : float 55 | """ 56 | return np.prod(np.array([box[i][1] - box[i][0] for i in range(3)])) * N / w 57 | 58 | @njit(numba.boolean(numba.float64[:, :], numba.int32, numba.float64, numba.float64, numba.int32, numba.int32)) 59 | def _is_resolved(box : npt.NDArray, N : int, w : float, sigma_T : float, Nmin : int, Nmax : int) -> bool: 60 | if N == 0: 61 | return False 62 | 63 | n = _calc_n(box, N, w) 64 | Nres = _calc_N_res(w, sigma_T, n) 65 | 66 | return N > 2 * min(Nmin, max(Nmin, Nres)) 67 | 68 | @njit 69 | def _is_inside(position : npt.NDArray, box : npt.NDArray) -> bool: 70 | a : bool = position[0] >= box[0][0] and position[0] <= box[0][1] 71 | b : bool = position[1] >= box[1][0] and position[1] <= box[1][1] 72 | c : bool = position[2] >= box[2][0] and position[2] <= box[2][1] 73 | 74 | return a and b and c 75 | 76 | @njit(numba.types.Tuple((numba.int64[:], numba.int64))(numba.int64[:], numba.float64[:, :], numba.float64[:, :], numba.int64, numba.int64), parallel=False) 77 | def _sort(permutations : npt.NDArray, box : npt.NDArray, positions : npt.NDArray, offset : int, N : int) -> tuple[npt.NDArray, int]: 78 | '''sort particles in cell 79 | 80 | Parameters 81 | ---------- 82 | box : np.ndarray 83 | cell 84 | positions : ndarray((3, )) 85 | particle positions 86 | offset : int 87 | number offset 88 | N : int 89 | number of particles to be considered 90 | 91 | Returns 92 | ------- 93 | new_permutations : ndarray[int] 94 | N : int 95 | number of found positions 96 | ''' 97 | new_permutations = np.copy(permutations) 98 | runner = offset 99 | Nnew = 0 100 | for i in numba.prange(offset, offset + N): 101 | p = new_permutations[i] 102 | if _is_inside(positions[p], box): 103 | com.swap(new_permutations, i, runner) 104 | runner += 1 105 | Nnew += 1 106 | 107 | return new_permutations, Nnew 108 | 109 | @njit 110 | def _create_boxes(box): 111 | half = np.array([0.5*(box[i][0] + box[i][1]) for i in range(3)]) 112 | 113 | child_geo1 = np.array(((half[0], box[0][1]), (half[1], box[1][1]), (half[2], box[2][1]))) 114 | child_geo2 = np.array(((box[0][0], half[0]), (half[1], box[1][1]), (half[2], box[2][1]))) 115 | child_geo3 = np.array(((box[0][0], half[0]), (box[1][0], half[1]), (half[2], box[2][1]))) 116 | child_geo4 = np.array(((half[0], box[0][1]), (box[1][0], half[1]), (half[2], box[2][1]))) 117 | 118 | child_geo5 = np.array(((half[0], box[0][1]), (half[1], box[1][1]), (box[2][0], half[2]))) 119 | child_geo6 = np.array(((box[0][0], half[0]), (half[1], box[1][1]), (box[2][0], half[2]))) 120 | child_geo7 = np.array(((box[0][0], half[0]), (box[1][0], half[1]), (box[2][0], half[2]))) 121 | child_geo8 = np.array(((half[0], box[0][1]), (box[1][0], half[1]), (box[2][0], half[2]))) 122 | 123 | return [child_geo1, child_geo2, child_geo3, child_geo4, child_geo5, child_geo6, child_geo7, child_geo8] 124 | 125 | @njit 126 | def _get_min_aspect_ratio(box, axis, half): 127 | half_loc = np.array([0.5*(half[i] - box[i][0]) for i in range(3)]) 128 | 129 | match axis: 130 | case 0: 131 | return min(half_loc[0] / half_loc[1], half_loc[0] / half_loc[2]); 132 | case 1: 133 | return min(half_loc[1] / half_loc[0], half_loc[1] / half_loc[2]); 134 | case 2: 135 | return min(half_loc[2] / half_loc[1], half_loc[2] / half_loc[0]); 136 | 137 | @njit 138 | def _devide(box, axis, half): 139 | box1 = np.copy(box) 140 | box2 = np.copy(box) 141 | 142 | box1[axis][0] = box[axis][0] 143 | box1[axis][1] = half[axis] 144 | 145 | box2[axis][0] = half[axis] 146 | box2[axis][1] = box[axis][1] 147 | 148 | return (box1, box2) 149 | 150 | @njit 151 | def _create_combined_boxes(box, min_aspect_ratio, half): 152 | boxes = np.empty((15, 3, 2)) 153 | boxes[0] = box 154 | N = 0 155 | Nold = 0 156 | q = 1 157 | 158 | for i in range(3): 159 | if _get_min_aspect_ratio(box, i, half) > min_aspect_ratio: 160 | for b in range(Nold, Nold + 2**N): 161 | new_boxes = _devide(boxes[b], i, half) 162 | boxes[q] = new_boxes[0] 163 | boxes[q + 1] = new_boxes[1] 164 | q += 2 165 | Nold += 2**N 166 | N += 1 167 | 168 | N = 2**N 169 | new_boxes = np.empty((N, 3, 2)) 170 | 171 | for b in range(N): 172 | new_boxes[b] = boxes[Nold + b] 173 | 174 | return new_boxes 175 | 176 | @njit 177 | def _get_centre_of_mass(permutations, positions, offset, n_elements): 178 | com = np.zeros(3) 179 | 180 | for i in range(offset, offset + n_elements): 181 | p = permutations[i] 182 | com += positions[p] 183 | 184 | return com / float(n_elements) 185 | 186 | class Type(Enum): 187 | COV = 0 188 | COM = 1 189 | 190 | class Leaf: 191 | def __init__(self): 192 | self.level = 0 193 | self.elem_offset = 0 194 | self.number_elements = 0 195 | self.id_parent = None 196 | self.id_first_child = None 197 | self.number_children = 0 198 | 199 | class Octree: 200 | def __init__(self): 201 | self.clear() 202 | self.min_aspect_ratio = 2.0/3.0 203 | self.type = Type.COV 204 | 205 | def clear(self): 206 | self.cell_boxes = [] 207 | self.leafs = [] 208 | self.sigma_T = 3.631681e-19 209 | self.w = 1.0 210 | self.Nmin = 8 211 | self.Nmax = 64 212 | self.max_level = 10 213 | self.permutations = [] 214 | self.cell_offsets = [] 215 | self.level = 0 216 | 217 | def build(self, positions): 218 | self.clear() 219 | self._create_root(positions) 220 | self.permutations = np.array([i for i in range(len(positions))]) 221 | 222 | for level in range(self.max_level): 223 | self.level += 1 224 | self.cell_offsets.append(self.cell_offsets[-1]) 225 | for i in range(self.cell_offsets[level], self.cell_offsets[level + 1]): 226 | self._progress(i, positions) 227 | 228 | if self.cell_offsets[level + 1] == self.cell_offsets[level + 2]: 229 | break 230 | 231 | def _create_root(self, positions): 232 | box = _find_bounding_box(positions) 233 | leaf = Leaf() 234 | leaf.number_elements = len(positions) 235 | 236 | self.cell_offsets += [0, 1] 237 | self.leafs.append(leaf) 238 | self.cell_boxes.append(box) 239 | 240 | def _progress(self, leaf_id, positions): 241 | if _is_resolved(self.cell_boxes[leaf_id], self.leafs[leaf_id].number_elements, self.w, self.sigma_T, self.Nmin, self.Nmax): 242 | 243 | self.leafs[leaf_id].id_first_child = self.cell_offsets[-1] 244 | 245 | if self.type == Type.COV: 246 | half = 0.5 * np.array([self.cell_boxes[leaf_id][i][1] + self.cell_boxes[leaf_id][i][0] for i in range(3)]) 247 | elif self.type == Type.COM: 248 | half = _get_centre_of_mass(self.permutations, positions, self.leafs[leaf_id].elem_offset, self.leafs[leaf_id].number_elements) 249 | 250 | new_boxes = _create_combined_boxes(self.cell_boxes[leaf_id], self.min_aspect_ratio, half) 251 | self.cell_offsets[-1] += len(new_boxes) 252 | self.leafs[leaf_id].number_children = len(new_boxes) 253 | 254 | for box in new_boxes: 255 | self.cell_boxes.append(box) 256 | 257 | else: 258 | pass 259 | 260 | offset = 0 261 | 262 | for i in range(self.leafs[leaf_id].number_children): 263 | new_leaf = Leaf() 264 | new_leaf.level = self.leafs[leaf_id].level + 1 265 | new_leaf.id_parent = leaf_id 266 | 267 | new_leaf.elem_offset = self.leafs[leaf_id].elem_offset + offset 268 | 269 | self.permutations, N = _sort(self.permutations, self.cell_boxes[self.leafs[leaf_id].id_first_child + i], positions, new_leaf.elem_offset, self.leafs[leaf_id].number_elements - offset) 270 | 271 | new_leaf.number_elements = N 272 | offset += N 273 | 274 | self.leafs.append(new_leaf) 275 | -------------------------------------------------------------------------------- /dsmc/dsmc.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from numba import njit 3 | from numba import prange 4 | import numba 5 | from . import particles as prt 6 | from . import octree as oc 7 | from . import common as com 8 | 9 | @njit(cache=True) 10 | def _push(velocities, positions, dt): 11 | old_positions = np.copy(positions) 12 | for p in prange(len(positions)): 13 | positions[p] = positions[p] + velocities[p]*dt 14 | return (velocities, positions, old_positions) 15 | 16 | @njit(cache=True) 17 | def _boundary(velocities, positions, old_positions, domain, boundary_conds): 18 | kept_parts = np.ones(positions.shape[0], dtype=np.uint) 19 | 20 | for p in prange(len(positions)): 21 | while not oc._is_inside(positions[p], domain) and kept_parts[p]: 22 | for i in range(3): 23 | if positions[p][i] < domain[i][0]: 24 | if boundary_conds[i][0] == 0: 25 | old_positions[p][i] = positions[p][i] 26 | positions[p][i] = 2.0 * domain[i][0] - positions[p][i] 27 | velocities[p][i] *= -1.0 28 | elif boundary_conds[i][0] == 1 or boundary_conds[i][0] == 2: 29 | kept_parts[p] = 0 30 | if positions[p][i] > domain[i][1]: 31 | if boundary_conds[i][1] == 0: 32 | old_positions[p][i] = positions[p][i] 33 | positions[p][i] = 2.0 * domain[i][1] - positions[p][i] 34 | velocities[p][i] *= -1.0 35 | elif boundary_conds[i][1] == 1 or boundary_conds[i][0] == 2: 36 | kept_parts[p] = 0 37 | 38 | N = int(sum(kept_parts)) 39 | p = 0 40 | new_velocities = np.empty((N, 3)) 41 | new_positions = np.empty((N, 3)) 42 | new_old_positions = np.empty((N, 3)) 43 | 44 | for i in range(positions.shape[0]): 45 | if kept_parts[i] == 1: 46 | new_velocities[p] = velocities[i] 47 | new_positions[p] = positions[i] 48 | new_old_positions[p] = old_positions[p] 49 | p += 1 50 | else: 51 | continue 52 | 53 | return (new_velocities, new_positions, new_old_positions) 54 | 55 | @njit(cache=True) 56 | def _check_positions(velocities, positions, old_positions, domain): 57 | kept_parts = np.ones(positions.shape[0], dtype=np.uint) 58 | 59 | for i in prange(positions.shape[0]): 60 | if (not oc._is_inside(positions[i], domain)) and (not oc._is_inside(old_positions[i], domain)): 61 | kept_parts[i] = 0 62 | 63 | N = sum(kept_parts) 64 | p = 0 65 | new_velocities = np.empty((N, 3)) 66 | new_positions = np.empty((N, 3)) 67 | new_old_positions = np.empty((N, 3)) 68 | 69 | for i in prange(positions.shape[0]): 70 | if kept_parts[i] == 1: 71 | new_velocities[p] = velocities[i] 72 | new_positions[p] = positions[i] 73 | new_old_positions[p] = old_positions[i] 74 | p += 1 75 | else: 76 | continue 77 | 78 | return (new_velocities, new_positions, new_old_positions) 79 | 80 | @njit(cache=True) 81 | def _check_created_particles(velocities, positions, obj): 82 | kept_parts = np.ones(positions.shape[0], dtype=np.uint) 83 | 84 | for i in prange(positions.shape[0]): 85 | if oc._is_inside(positions[i], obj): 86 | kept_parts[i] = 0 87 | 88 | N = sum(kept_parts) 89 | p = 0 90 | new_velocities = np.empty((N, 3)) 91 | new_positions = np.empty((N, 3)) 92 | 93 | for i in prange(positions.shape[0]): 94 | if kept_parts[i] == 1: 95 | new_velocities[p] = velocities[i] 96 | new_positions[p] = positions[i] 97 | p += 1 98 | else: 99 | continue 100 | 101 | return (new_velocities, new_positions) 102 | 103 | @njit(cache=True) 104 | def _object(velocities, positions, old_positions, coll_obj): 105 | for p in range(positions.shape[0]): 106 | if oc._is_inside(positions[p], coll_obj): 107 | for i in range(3): 108 | if (old_positions[p][i] < coll_obj[i][0]): 109 | old_positions[p][i] = positions[p][i] 110 | positions[p][i] = 2.0 * coll_obj[i][0] - positions[p][i] 111 | velocities[p][i] *= -1.0 112 | 113 | if (old_positions[p][i] > coll_obj[i][1]): 114 | old_positions[p][i] = positions[p][i] 115 | positions[p][i] = 2.0 * coll_obj[i][1] - positions[p][i] 116 | velocities[p][i] *= -1.0 117 | 118 | return (velocities, positions, old_positions) 119 | 120 | @njit(cache=True) 121 | def _calc_prob(rel_vel : float, sigma_T : float, Vc : float, dt : float, w : float, N : int) -> np.single: 122 | """ 123 | Parameters 124 | ---------- 125 | vel1 : velocity 126 | vel2 : velocity 127 | sigma_T : float 128 | total cross section 129 | Vc : float 130 | cell volume 131 | w : float 132 | weight 133 | N : int 134 | number of particles 135 | 136 | Returns 137 | ------- 138 | collision proability : float 139 | """ 140 | return rel_vel * sigma_T * dt * w * N / Vc; 141 | 142 | @njit(numba.types.Tuple((numba.float64[:], numba.float64[:]))(numba.float64[:], numba.float64[:], numba.float64, numba.float64, numba.float64, numba.float64, numba.float64)) 143 | def _calc_post_col_vels(velocity1 : np.ndarray, velocity2 : np.ndarray, mass1 : float, mass2 : float, rel_vel_module : float, rand_number1 : float, rand_number2 : float) -> tuple[np.ndarray, np.ndarray]: 144 | mass12 = (mass1 + mass2) 145 | mass1_12 = (mass1 / mass12) 146 | mass2_12 = (mass2 / mass12) 147 | 148 | cos_xi = (2.0 * rand_number1 - 1.0) 149 | sin_xi = (np.sqrt(1.0 - cos_xi * cos_xi)) 150 | epsilon = (2.0 * np.pi * rand_number2) 151 | 152 | centre_of_mass_velocity = (velocity1 * mass1 + velocity2 * mass2) * (1.0 / mass12) 153 | 154 | rel_velocity_new = np.empty((3, )) 155 | 156 | rel_velocity_new[0] = rel_vel_module * cos_xi 157 | rel_velocity_new[1] = rel_vel_module * sin_xi * np.cos(epsilon) 158 | rel_velocity_new[2] = rel_vel_module * sin_xi * np.sin(epsilon) 159 | 160 | return (centre_of_mass_velocity + rel_velocity_new * mass2_12 , centre_of_mass_velocity - rel_velocity_new * mass1_12) 161 | 162 | @njit(numba.float64[:, :](numba.int64[:], numba.float64[:, :], numba.float64, numba.float64, numba.float64, numba.float64, numba.float64, numba.int64, numba.int64)) 163 | def _update_velocities(permutations : np.ndarray, velocities : np.ndarray, mass : float, sigma_T : float, Vc : float, dt : float, w : float, offset : int, N : int) -> np.ndarray: 164 | for i in range(1, N, 2): 165 | p1 = permutations[offset + i - 1] 166 | p2 = permutations[offset + i] 167 | rel_vel = np.linalg.norm(velocities[p1] - velocities[p2]) 168 | P = _calc_prob(rel_vel, sigma_T, Vc, dt, w, N) 169 | R = np.random.random(3) 170 | 171 | if R[0] < P: 172 | new_vels = _calc_post_col_vels(velocities[p1], velocities[p2], mass, mass, rel_vel, R[1], R[2]) 173 | velocities[p1] = new_vels[0] 174 | velocities[p2] = new_vels[1] 175 | 176 | return velocities 177 | 178 | @njit(numba.float64[:, :](numba.int64[:], numba.float64[:, :], numba.float64, numba.float64, numba.float64, numba.float64, numba.int64[:], numba.int64[:], numba.int64[:], numba.float64[:, : , :], numba.int64)) 179 | def _update_vels(permutations : np.ndarray, velocities : np.ndarray, mass : float, sigma_T : float, dt : float, w : float, elem_offsets : np.ndarray, number_elements : np.ndarray, number_children : np.ndarray, cell_boxes : np.ndarray, Nleafs : int) -> np.ndarray: 180 | for i in range(Nleafs): 181 | if not number_children[i] and number_elements[i]: 182 | Vc = com.get_V(cell_boxes[i]) 183 | velocities = _update_velocities(permutations, velocities, mass, sigma_T, Vc, dt, w, elem_offsets[i], number_elements[i]) 184 | 185 | return velocities 186 | 187 | @njit(cache=True) 188 | def _get_boundary(boundary): 189 | if boundary == "xmin": 190 | return (0, 0) 191 | elif boundary == "xmax": 192 | return (0, 1) 193 | elif boundary == "ymin": 194 | return (1, 0) 195 | elif boundary == "ymax": 196 | return (1, 1) 197 | elif boundary == "zmin": 198 | return (2, 0) 199 | elif boundary == "zmax": 200 | return (2, 1) 201 | 202 | @njit(cache=True) 203 | def _get_bc_type(bc_type): 204 | if bc_type == "ela": 205 | return 0 206 | elif bc_type == "open": 207 | return 1 208 | elif bc_type == "inflow": 209 | return 2 210 | 211 | class Boundary: 212 | def __init__(self): 213 | self.T = np.ones((3, 2))*300.0 214 | self.n = np.ones((3, 2))*1e+18 215 | self.u = np.zeros((3, 2, 3)) 216 | 217 | class DSMC: 218 | def __init__(self): 219 | self.clear() 220 | 221 | def clear(self): 222 | self.particles = prt.Particles() 223 | self.octree = oc.Octree() 224 | self.w = None 225 | self.domain = None 226 | self.boundary_conds = np.array([[0, 0], [0, 0], [0, 0]], dtype=np.uint) # 0 = ela, 1 = open, 2 = inflow 227 | self.boundary = Boundary() 228 | self.sigma_T = 3.631681e-19 229 | self.mass = None 230 | self.objects = [] 231 | 232 | def advance(self, dt, collisions=True, octree=True): 233 | if self.domain is None: 234 | raise Exception("simulation domain not defined") 235 | if self.particles.N == 0: 236 | print("warning: no particles in domain") 237 | if self.w == None: 238 | raise Exception("particle weight not set") 239 | 240 | for i in range(3): 241 | for j in range(2): 242 | if self.boundary_conds[i][j] == 2: 243 | self.particles.inflow(self.mass, self.boundary.T[i][j], self.boundary.u[i][j], self.boundary.n[i][j], self.w, dt, self.domain, i, j) 244 | 245 | velocities, positions, old_positions = _push(self.particles.Vel, self.particles.Pos, dt) 246 | velocities, positions, old_positions = _check_positions(velocities, positions, old_positions, self.domain) 247 | 248 | 249 | for obj in self.objects: 250 | velocities, positions, old_positions = _object(velocities, positions, old_positions, obj) 251 | 252 | velocities, positions, old_positions = _boundary(velocities, positions, old_positions, self.domain, self.boundary_conds) 253 | 254 | if octree: 255 | self.octree.build(positions) 256 | if collisions and octree: 257 | velocities = self._update_velocities(dt, velocities) 258 | 259 | self.particles.VelPos = (velocities, positions) 260 | 261 | def _update_velocities(self, dt, velocities): 262 | Nleafs : int = len(self.octree.leafs) 263 | elem_offsets : np.ndarray = np.array([leaf.elem_offset for leaf in self.octree.leafs], dtype=int) 264 | number_elements : np.ndarray = np.array([leaf.number_elements for leaf in self.octree.leafs], dtype=int) 265 | number_children : np.ndarray = np.array([leaf.number_children for leaf in self.octree.leafs], dtype=int) 266 | cell_boxes : np.ndarray = np.array([box for box in self.octree.cell_boxes]) 267 | 268 | return _update_vels(self.octree.permutations, velocities, self.mass, self.sigma_T, dt, self.w, elem_offsets, number_elements, number_children, cell_boxes, Nleafs) 269 | 270 | def create_particles(self, box, T, n, u = np.zeros(3)): 271 | box = np.array(box) 272 | N = int(round(com.get_V(box) * n / self.w)) 273 | print("creating {} particles".format(N)) 274 | self.particles.create_particles(box, self.mass, T, N, u) 275 | 276 | for obj in self.objects: 277 | self.particles.VelPos = _check_created_particles(self.particles.Vel, self.particles.Pos, obj) 278 | 279 | print("now containing {} particles, {} total".format(N, self.particles.N)) 280 | 281 | def set_domain(self, domain): 282 | self.domain = np.array(domain) 283 | 284 | def set_mass(self, mass): 285 | self.mass = mass 286 | 287 | def set_weight(self, w): 288 | self.octree.w = w 289 | self.w = w 290 | 291 | def set_bc_type(self, boundary, bc_type): 292 | bound = _get_boundary(boundary) 293 | bc = _get_bc_type(bc_type) 294 | 295 | self.boundary_conds[bound[0]][bound[1]] = bc 296 | 297 | print("boundary [" + boundary + "] set to [" + bc_type + "]") 298 | 299 | def set_bc_values(self, boundary, T, n, u): 300 | i, j = _get_boundary(boundary) 301 | 302 | self.boundary.T[i][j] = T 303 | self.boundary.n[i][j] = n 304 | self.boundary.u[i][j] = u 305 | 306 | print("boundary [" + boundary + "] set to values T : {}, n : {}, u : {}".format(T, n, u)) 307 | 308 | def add_object(self, coll_object): 309 | self.objects.append(np.array(coll_object)) -------------------------------------------------------------------------------- /tests/unit/test_dsmc/octree.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | import numpy as np 3 | from dsmc import octree as oc 4 | from dsmc import common as com 5 | import csv 6 | 7 | class TestOctree(unittest.TestCase): 8 | def test__find_bounding_box(self): 9 | positions = np.array([(0.0, 0.0, -1.0), (-2.0, -3.0, 0.0), (4.0, 5.0, 0.0)]) 10 | box = oc._find_bounding_box(positions) 11 | 12 | self.assertEqual(-2.0, box[0][0]) 13 | self.assertEqual(4.0, box[0][1]) 14 | 15 | self.assertEqual(-3.0, box[1][0]) 16 | self.assertEqual(5.0, box[1][1]) 17 | 18 | self.assertEqual(-1.0, box[2][0]) 19 | self.assertEqual(0.0, box[2][1]) 20 | 21 | def test__calc_N_res(self): 22 | w = 1.0e+9 23 | sigma_T = 1.0e-16 24 | n = 1.0e+17 25 | ref = int(round(np.sqrt(2) / (32.0 * w * sigma_T**3 * n**2))) 26 | N = oc._calc_N_res(w, sigma_T, n) 27 | 28 | self.assertEqual(ref, N) 29 | 30 | def test__calc_n(self): 31 | box = ((0, 1), (2, 4), (4, 7)) 32 | N = 300 33 | w = 100 34 | res = oc._calc_n(box, N, w) 35 | 36 | self.assertEqual(18.0, res) 37 | 38 | def test__is_inside(self): 39 | box = [[2.0, 3.0], [4.0, 6.0], [-1.0, 1.0]] 40 | box = np.array(box) 41 | position1 = np.array([2.5, 5.0, 0.0]) 42 | position2 = np.array([0.0, 0.0, 0.0]) 43 | position3 = np.array([2.5, 6.0, 0.5]) 44 | 45 | self.assertTrue(oc._is_inside(position1, box)) 46 | self.assertFalse(oc._is_inside(position2, box)) 47 | self.assertTrue(oc._is_inside(position3, box)) 48 | 49 | def test_sort(self): 50 | box = np.array([[0.0, 1.0], [0.0, 1.0], [0.0, 1.0]]) 51 | positions1 = np.random.random((100, 3)) 52 | positions2 = np.random.random((200, 3)) - np.ones((200, 3))*2 53 | positions = np.concatenate((positions2, positions1, positions2)) 54 | permutations1 = np.array([i for i in range(len(positions2))]) 55 | permutations2 = np.array([i for i in range(len(positions2), len(positions))]) 56 | np.random.shuffle(permutations2) 57 | permutations = np.concatenate((permutations1, permutations2)) 58 | offset = len(positions2) 59 | N = len(positions1) + len(positions2) 60 | count = 0 61 | 62 | for position in positions1: 63 | self.assertTrue(oc._is_inside(position, box)) 64 | 65 | for position in positions2: 66 | self.assertFalse(oc._is_inside(position, box)) 67 | 68 | for position in positions: 69 | if oc._is_inside(position, box): 70 | count += 1 71 | 72 | self.assertEqual(len(positions1), count) 73 | 74 | self.assertEqual(len(positions2), len(permutations1)) 75 | self.assertEqual(len(positions1) + len(positions2), len(permutations2)) 76 | self.assertEqual(len(positions), len(permutations)) 77 | 78 | permutations, Nnew = oc._sort(permutations, box, positions, offset, N) 79 | 80 | self.assertEqual(Nnew, len(positions1)) 81 | 82 | for i in range(offset, offset + Nnew): 83 | p = permutations[i] 84 | self.assertTrue(oc._is_inside(positions[p], box)) 85 | 86 | for i in range(offset + Nnew, len(permutations)): 87 | p = permutations[i] 88 | self.assertFalse(oc._is_inside(positions[p], box)) 89 | 90 | def test_sort2(self): 91 | box = np.array([[0.0, 1.0], [0.0, 1.0], [0.0, 1.0]]) 92 | N = 20 93 | Nh = 10 94 | Nm = 15 95 | Np = 5 96 | positions = np.empty((N, 3)) 97 | positions1 = np.empty((Np, 3)) 98 | positions2 = np.empty((Np, 3)) 99 | positions3 = np.empty((Nh, 3)) 100 | permutations = np.array([i for i in range(N)]) 101 | 102 | for i in range(Np): 103 | positions1[i] = np.random.random(3) - np.ones(3) 104 | 105 | for i in range(Np): 106 | positions2[i] = np.random.random(3) 107 | 108 | for i in range(Nh): 109 | positions3[i] = np.random.random(3) - np.ones(3) 110 | 111 | positions = np.concatenate((positions3, positions1, positions2)) 112 | permutations, Nnew = oc._sort(permutations, box, positions, Nh, Nh) 113 | 114 | self.assertEqual(Nnew, Np) 115 | 116 | for i in range(Nh): 117 | p = permutations[i] 118 | pos = positions[p] 119 | a = not (pos[0] <= box[0][1]) 120 | b = not (pos[0] >= box[0][0]) 121 | 122 | c = not (pos[1] <= box[1][1]) 123 | d = not (pos[1] >= box[1][0]) 124 | 125 | e = not (pos[2] <= box[2][1]) 126 | f = not (pos[2] >= box[2][0]) 127 | 128 | self.assertTrue(a or b or c or d or e or f) 129 | 130 | for i in range(Nm, N): 131 | p = permutations[i] 132 | pos = positions[p] 133 | a = not (pos[0] <= box[0][1]) 134 | b = not (pos[0] >= box[0][0]) 135 | 136 | c = not (pos[1] <= box[1][1]) 137 | d = not (pos[1] >= box[1][0]) 138 | 139 | e = not (pos[2] <= box[2][1]) 140 | f = not (pos[2] >= box[2][0]) 141 | 142 | self.assertTrue(a or b or c or d or e or f) 143 | 144 | for i in range(Nh, Nm): 145 | p = permutations[i] 146 | pos = positions[p] 147 | a = (pos[0] <= box[0][1]) 148 | b = (pos[0] >= box[0][0]) 149 | 150 | c = (pos[1] <= box[1][1]) 151 | d = (pos[1] >= box[1][0]) 152 | 153 | e = (pos[2] <= box[2][1]) 154 | f = (pos[2] >= box[2][0]) 155 | 156 | self.assertTrue(a and b and c and d and e and f) 157 | 158 | 159 | def load_particles(self): 160 | positions = [] 161 | 162 | with open("./test_data/particles.csv", "r", newline='') as csvfile: 163 | reader = csv.reader(csvfile, delimiter=',') 164 | for row in reader: 165 | positions.append([float(row[i]) for i in range(3)]) 166 | 167 | return np.array(positions) 168 | 169 | def test_sort3(self): 170 | box = np.array([[-1.0, 1.0], [-1.0, 1.0], [-1.0, 1.0]]) 171 | boxes = [] + oc._create_boxes(box) 172 | N = 100 173 | permutations = np.array([i for i in range(N)]) 174 | positions = self.load_particles() 175 | 176 | permutations , Np1 = oc._sort(permutations, boxes[0], positions, 0, N) 177 | permutations , Np2 = oc._sort(permutations, boxes[1], positions, Np1, N - Np1) 178 | permutations , Np3 = oc._sort(permutations, boxes[2], positions, Np1 + Np2, N - Np2 - Np1) 179 | #permutations , Np4 = oc._sort(permutations, boxes[3], positions, Np3, N - Np3) 180 | 181 | #permutations , Np5 = oc._sort(permutations, boxes[4], positions, Np4, N - Np4) 182 | #permutations , Np6 = oc._sort(permutations, boxes[5], positions, Np5, N - Np5) 183 | #permutations , Np7 = oc._sort(permutations, boxes[6], positions, Np6, N - Np6) 184 | #permutations , Np8 = oc._sort(permutations, boxes[7], positions, Np7, N - Np7) 185 | 186 | Nnew = np.zeros(8, dtype=int) 187 | 188 | for i in range(Np1): 189 | p = permutations[i] 190 | pos = positions[p] 191 | if oc._is_inside(pos, boxes[0]): 192 | Nnew[0] += 1 193 | 194 | self.assertEqual(Nnew[0], Np1) 195 | 196 | for i in range(Np1, Np1 + Np2): 197 | p = permutations[i] 198 | pos = positions[p] 199 | if oc._is_inside(pos, boxes[1]): 200 | Nnew[1] += 1 201 | 202 | self.assertEqual(Nnew[1], Np2) 203 | 204 | for i in range(Np1 + Np2, Np1 + Np2 + Np3): 205 | p = permutations[i] 206 | pos = positions[p] 207 | if oc._is_inside(pos, boxes[2]): 208 | Nnew[2] += 1 209 | 210 | self.assertEqual(Nnew[2], Np3) 211 | 212 | def test__create_boxes(self): 213 | box_orig = np.array([[-1.0, 1.0], [-1.0, 1.0], [-1.0, 1.0]]) 214 | boxes = oc._create_boxes(box_orig) 215 | 216 | self.assertEqual(8, len(boxes)) 217 | V = 0.0 218 | 219 | for box in boxes: 220 | V += com.get_V(box) 221 | 222 | self.assertEqual(com.get_V(box_orig), V) 223 | 224 | def test__get_min_aspect_ratio_1(self): 225 | box = np.array([(0.0, 1.0), (0.0, 10.0), (0.0, 100.0)]) 226 | half = 0.5 * np.array([box[i][1] + box[i][0] for i in range(3)]) 227 | axis1 = 0 228 | axis2 = 1 229 | axis3 = 2 230 | 231 | self.assertEqual(0.01, oc._get_min_aspect_ratio(box, axis1, half)) 232 | self.assertEqual(0.1, oc._get_min_aspect_ratio(box, axis2, half)) 233 | self.assertEqual(10.0, oc._get_min_aspect_ratio(box, axis3, half)) 234 | 235 | def test__get_min_aspect_ratio_2(self): 236 | box = np.array([(-1.0, 1.0), (-10.0, 10.0), (-100.0, 100.0)]) 237 | half = 0.5 * np.array([box[i][1] + box[i][0] for i in range(3)]) 238 | axis1 = 0 239 | axis2 = 1 240 | axis3 = 2 241 | 242 | self.assertEqual(0.01, oc._get_min_aspect_ratio(box, axis1, half)) 243 | self.assertEqual(0.1, oc._get_min_aspect_ratio(box, axis2, half)) 244 | self.assertEqual(10.0, oc._get_min_aspect_ratio(box, axis3, half)) 245 | 246 | def test__devide(self): 247 | box = np.array([(0.0, 1.0), (0.0, 10.0), (0.0, 100.0)]) 248 | half = 0.5 * np.array([box[i][1] + box[i][0] for i in range(3)]) 249 | box_x1, box_x2 = oc._devide(box, 0, half) 250 | box_y1, box_y2 = oc._devide(box, 1, half) 251 | box_z1, box_z2 = oc._devide(box, 2, half) 252 | 253 | boxes = ((box_x1, box_x2), (box_y1, box_y2), (box_z1, box_z2)) 254 | 255 | half = np.array([0.5*(box[i][0] + box[i][1]) for i in range(3)]) 256 | 257 | for b in range(3): 258 | box_a = boxes[b][0] 259 | box_b = boxes[b][1] 260 | 261 | self.assertEqual(box_a[b][0], box[b][0]) 262 | self.assertEqual(box_a[b][1], half[b]) 263 | 264 | self.assertEqual(box_b[b][0], half[b]) 265 | self.assertEqual(box_b[b][1], box[b][1]) 266 | 267 | for i in range(3): 268 | for j in range(2): 269 | if b != i: 270 | self.assertEqual(box_a[i][j], box[i][j]) 271 | self.assertEqual(box_b[i][j], box[i][j]) 272 | 273 | def test__create_combined_boxes_1(self): 274 | box = np.array([(0.0, 1.0), (0.0, 10.0), (0.0, 100.0)]) 275 | half = 0.5 * np.array([box[i][1] + box[i][0] for i in range(3)]) 276 | min_aspect_ratio = 0.0 277 | boxes_old = oc._create_boxes(box) 278 | boxes_new = oc._create_combined_boxes(box, min_aspect_ratio, half) 279 | V = 0.0 280 | 281 | for b in boxes_new: 282 | V += com.get_V(b) 283 | 284 | self.assertEqual(com.get_V(box), V) 285 | self.assertEqual(len(boxes_old), len(boxes_new)) 286 | 287 | def test__create_combined_boxes_2(self): 288 | box = np.array([(0.0, 1.0), (0.0, 10.0), (0.0, 100.0)]) 289 | half = 0.5 * np.array([box[i][1] + box[i][0] for i in range(3)]) 290 | min_aspect_ratio = 0.05 291 | boxes_new = oc._create_combined_boxes(box, min_aspect_ratio, half) 292 | V = 0.0 293 | 294 | for b in boxes_new: 295 | V += com.get_V(b) 296 | 297 | self.assertEqual(com.get_V(box), V) 298 | self.assertEqual(4, len(boxes_new)) 299 | 300 | def test__create_combined_boxes_3(self): 301 | box = np.array([(-1.0, 1.0), (-10.0, 10.0), (-100.0, 100.0)]) 302 | half = 0.5 * np.array([box[i][1] + box[i][0] for i in range(3)]) 303 | min_aspect_ratio = 0.05 304 | boxes_new = oc._create_combined_boxes(box, min_aspect_ratio, half) 305 | V = 0.0 306 | 307 | for b in boxes_new: 308 | V += com.get_V(b) 309 | 310 | self.assertEqual(com.get_V(box), V) 311 | self.assertEqual(4, len(boxes_new)) 312 | 313 | def test__create_combined_boxes_4(self): 314 | box = np.array([(-1.0, 1.0), (-10.0, 10.0), (-100.0, 100.0)]) 315 | half = 0.5 * np.array([box[i][1] + box[i][0] for i in range(3)]) 316 | min_aspect_ratio = 0.0 317 | boxes_new = oc._create_combined_boxes(box, min_aspect_ratio, half) 318 | V = 0.0 319 | 320 | for b in boxes_new: 321 | V += com.get_V(b) 322 | 323 | self.assertEqual(com.get_V(box), V) 324 | self.assertEqual(8, len(boxes_new)) 325 | 326 | 327 | def test__get_centre_of_mass(self): 328 | permutations = np.array([i for i in range(4)]) 329 | positions = np.array([[-1.0, -1.0, 0.0], [1.0, -1.0, 0.0], [1.0, 1.0, 0.0], [-1.0, 1.0, 0.0]]) 330 | offset = 0 331 | n_elements = 4 332 | 333 | centre_of_mass = oc._get_centre_of_mass(permutations, positions, offset, n_elements) 334 | 335 | self.assertEqual(0.0, centre_of_mass[0]) 336 | self.assertEqual(0.0, centre_of_mass[1]) 337 | self.assertEqual(0.0, centre_of_mass[2]) 338 | 339 | class TestOctreeOctree(unittest.TestCase): 340 | def test_build(self): 341 | positions = np.random.random((1000, 3))*2.0 - np.ones((1000, 3)) 342 | octree = oc.Octree() 343 | octree.w = 1e+18 344 | 345 | octree.build(positions) 346 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 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Such new versions will 567 | be similar in spirit to the present version, but may differ in detail to 568 | address new problems or concerns. 569 | 570 | Each version is given a distinguishing version number. If the 571 | Program specifies that a certain numbered version of the GNU General 572 | Public License "or any later version" applies to it, you have the 573 | option of following the terms and conditions either of that numbered 574 | version or of any later version published by the Free Software 575 | Foundation. If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT 593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY 594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, 595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM 597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF 598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION. 599 | 600 | 16. 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Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | --------------------------------------------------------------------------------