mirror of
https://github.com/smyalygames/FiniteVolumeGPU.git
synced 2025-11-27 23:29:49 +01:00
341 lines
9.6 KiB
Python
341 lines
9.6 KiB
Python
# -*- coding: utf-8 -*-
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"""
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This python module implements Cuda context handling
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Copyright (C) 2018 SINTEF ICT
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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"""
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import gc
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import numpy as np
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from GPUSimulators.simulator.boundary import BoundaryCondition
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def get_extent(width, height, nx, ny, grid, index=None):
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if grid is not None:
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gx = grid.x
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gy = grid.y
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if index is not None:
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i, j = grid.get_coordinate(index)
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else:
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i, j = grid.get_coordinate()
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dx = (width / gx) / nx
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dy = (height / gy) / ny
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x0 = width * i / gx + 0.5 * dx
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y0 = height * j / gy + 0.5 * dy
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x1 = width * (i + 1) / gx - 0.5 * dx
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y1 = height * (j + 1) / gy - 0.5 * dx
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else:
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dx = width / nx
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dy = height / ny
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x0 = 0.5 * dx
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y0 = 0.5 * dy
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x1 = width - 0.5 * dx
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y1 = height - 0.5 * dy
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return [x0, x1, y0, y1, dx, dy]
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def downsample(highres_solution, x_factor, y_factor=None):
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if y_factor is None:
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y_factor = x_factor
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assert (highres_solution.shape[1] % x_factor == 0)
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assert (highres_solution.shape[0] % y_factor == 0)
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if x_factor * y_factor == 1:
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return highres_solution
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if len(highres_solution.shape) == 1:
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highres_solution = highres_solution.reshape((1, highres_solution.size))
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nx = highres_solution.shape[1] / x_factor
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ny = highres_solution.shape[0] / y_factor
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return highres_solution.reshape([int(ny), int(y_factor), int(nx), int(x_factor)]).mean(3).mean(1)
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def bump(nx: int, ny: int, width: int, height: int,
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bump_size=None,
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ref_nx=None, ref_ny=None,
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x_center=0.5, y_center=0.5,
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h_ref=0.5, h_amp=0.1, u_ref=0.0, u_amp=0.1, v_ref=0.0, v_amp=0.1):
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if ref_nx is None:
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ref_nx = nx
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assert (ref_nx >= nx)
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if ref_ny is None:
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ref_ny = ny
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assert (ref_ny >= ny)
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if bump_size is None:
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bump_size = width / 5.0
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ref_dx = width / float(ref_nx)
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ref_dy = height / float(ref_ny)
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x_center = ref_dx * ref_nx * x_center
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y_center = ref_dy * ref_ny * y_center
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x = ref_dx * (np.arange(0, ref_nx, dtype=np.float32) + 0.5) - x_center
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y = ref_dy * (np.arange(0, ref_ny, dtype=np.float32) + 0.5) - y_center
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xv, yv = np.meshgrid(x, y, sparse=False, indexing='xy')
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r = np.sqrt(xv ** 2 + yv ** 2)
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xv = None
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yv = None
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gc.collect()
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# Generate highres then downsample
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# h_highres = 0.5 + 0.1*np.exp(-(xv**2/size + yv**2/size))
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h_highres = h_ref + h_amp * 0.5 * (1.0 + np.cos(np.pi * r / bump_size)) * (r < bump_size)
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h = downsample(h_highres, ref_nx / nx, ref_ny / ny)
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h_highres = None
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gc.collect()
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# hu_highres = 0.1*np.exp(-(xv**2/size + yv**2/size))
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u_highres = u_ref + u_amp * 0.5 * (1.0 + np.cos(np.pi * r / bump_size)) * (r < bump_size)
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hu = downsample(u_highres, ref_nx / nx, ref_ny / ny) * h
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u_highres = None
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gc.collect()
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# hu_highres = 0.1*np.exp(-(xv**2/size + yv**2/size))
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v_highres = v_ref + v_amp * 0.5 * (1.0 + np.cos(np.pi * r / bump_size)) * (r < bump_size)
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hv = downsample(v_highres, ref_nx / nx, ref_ny / ny) * h
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v_highres = None
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gc.collect()
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dx = width / nx
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dy = height / ny
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return h, hu, hv, dx, dy
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def gen_shock_bubble(nx, ny, gamma, grid=None):
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"""
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Generate a Shock-bubble interaction case for the Euler equations
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"""
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width = 4.0
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height = 1.0
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g = 0.0
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rho = np.ones((ny, nx), dtype=np.float32)
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u = np.zeros((ny, nx), dtype=np.float32)
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v = np.zeros((ny, nx), dtype=np.float32)
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E = np.zeros((ny, nx), dtype=np.float32)
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p = np.ones((ny, nx), dtype=np.float32)
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x0, x1, y0, y1, dx, dy = get_extent(width, height, nx, ny, grid)
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x = np.linspace(x0, x1, nx, dtype=np.float32)
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y = np.linspace(y0, y1, ny, dtype=np.float32)
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xv, yv = np.meshgrid(x, y, sparse=False, indexing='xy')
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# Bubble
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radius = 0.25
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x_center = 0.5
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y_center = 0.5
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bubble = np.sqrt((xv - x_center) ** 2 + (yv - y_center) ** 2) <= radius
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rho = np.where(bubble, 0.1, rho)
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# Left boundary
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left = (xv < 0.1)
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rho = np.where(left, 3.81250, rho)
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u = np.where(left, 2.57669, u)
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# Energy
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p = np.where(left, 10.0, p)
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E = 0.5 * rho * (u ** 2 + v ** 2) + p / (gamma - 1.0)
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bc = BoundaryCondition({
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'north': BoundaryCondition.Type.Reflective,
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'south': BoundaryCondition.Type.Reflective,
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'east': BoundaryCondition.Type.Periodic,
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'west': BoundaryCondition.Type.Periodic
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})
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# Construct simulator
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arguments = {
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'rho': rho, 'rho_u': rho * u, 'rho_v': rho * v, 'E': E,
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'nx': nx, 'ny': ny,
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'dx': dx, 'dy': dy,
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'g': g,
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'gamma': gamma,
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'boundary_conditions': bc
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}
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return arguments
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def gen_kelvin_helmholtz(nx, ny, gamma, roughness=0.125, grid=None, index=None):
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"""
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Roughness parameter in (0, 1.0] determines how "squiggly"
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the interface between the zones is
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"""
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def gen_zones(nx, ny, n):
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"""
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Generates the zones of the two fluids of K-H
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"""
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zone = np.zeros((ny, nx), dtype=np.int32)
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def gen_smooth_random(nx, n):
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n = max(1, min(n, nx))
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if n == nx:
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return np.random.random(nx) - 0.5
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else:
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from scipy.interpolate import interp1d
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# Control points and interpolator
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xp = np.linspace(0.0, 1.0, n)
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yp = np.random.random(n) - 0.5
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if n == 1:
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kind = 'nearest'
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elif n == 2:
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kind = 'linear'
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elif n == 3:
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kind = 'quadratic'
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else:
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kind = 'cubic'
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f = interp1d(xp, yp, kind=kind)
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# Interpolation points
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x = np.linspace(0.0, 1.0, nx)
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return f(x)
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x0, x1, y0, y1, _, dy = get_extent(1.0, 1.0, nx, ny, grid, index)
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x = np.linspace(x0, x1, nx)
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y = np.linspace(y0, y1, ny)
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_, y = np.meshgrid(x, y)
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# print(y+a[0])
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a = gen_smooth_random(nx, n) * dy
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zone = np.where(y > 0.25 + a, zone, 1)
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a = gen_smooth_random(nx, n) * dy
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zone = np.where(y < 0.75 + a, zone, 1)
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return zone
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width = 2.0
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height = 1.0
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g = 0.0
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gamma = 1.4
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rho = np.empty((ny, nx), dtype=np.float32)
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u = np.empty((ny, nx), dtype=np.float32)
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v = np.zeros((ny, nx), dtype=np.float32)
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p = 2.5 * np.ones((ny, nx), dtype=np.float32)
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# Generate the different zones
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zones = gen_zones(nx, ny, max(1, min(nx, int(nx * roughness))))
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# Zone 0
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zone0 = zones == 0
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rho = np.where(zone0, 1.0, rho)
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u = np.where(zone0, 0.5, u)
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# Zone 1
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zone1 = zones == 1
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rho = np.where(zone1, 2.0, rho)
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u = np.where(zone1, -0.5, u)
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E = 0.5 * rho * (u ** 2 + v ** 2) + p / (gamma - 1.0)
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_, _, _, _, dx, dy = get_extent(width, height, nx, ny, grid, index)
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bc = BoundaryCondition({
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'north': BoundaryCondition.Type.Periodic,
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'south': BoundaryCondition.Type.Periodic,
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'east': BoundaryCondition.Type.Periodic,
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'west': BoundaryCondition.Type.Periodic
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})
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# Construct simulator
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arguments = {
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'rho': rho, 'rho_u': rho * u, 'rho_v': rho * v, 'E': E,
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'nx': nx, 'ny': ny,
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'dx': dx, 'dy': dy,
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'g': g,
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'gamma': gamma,
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'boundary_conditions': bc
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}
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return arguments
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def gen_rayleigh_taylor(nx, ny, gamma, version=0, grid=None):
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"""
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Generates a Rayleigh-Taylor instability case
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"""
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width = 0.5
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height = 1.5
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g = 0.1
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rho = np.zeros((ny, nx), dtype=np.float32)
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u = np.zeros((ny, nx), dtype=np.float32)
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v = np.zeros((ny, nx), dtype=np.float32)
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p = np.zeros((ny, nx), dtype=np.float32)
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x0, x1, y0, y1, dx, dy = get_extent(width, height, nx, ny, grid)
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x = np.linspace(x0, x1, nx, dtype=np.float32) - width * 0.5
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y = np.linspace(y0, y1, ny, dtype=np.float32) - height * 0.5
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xv, yv = np.meshgrid(x, y, sparse=False, indexing='xy')
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# This gives a squiggly interfaction
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if version == 0:
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y_threshold = 0.01 * np.cos(2 * np.pi * np.abs(x) / 0.5)
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rho = np.where(yv <= y_threshold, 1.0, rho)
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rho = np.where(yv > y_threshold, 2.0, rho)
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elif version == 1:
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rho = np.where(yv <= 0.0, 1.0, rho)
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rho = np.where(yv > 0.0, 2.0, rho)
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v = 0.01 * (1.0 + np.cos(2 * np.pi * xv / 0.5)) / 4
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else:
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assert False, "Invalid version"
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p = 2.5 - rho * g * yv
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E = 0.5 * rho * (u ** 2 + v ** 2) + p / (gamma - 1.0)
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bc = BoundaryCondition({
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'north': BoundaryCondition.Type.Reflective,
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'south': BoundaryCondition.Type.Reflective,
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'east': BoundaryCondition.Type.Reflective,
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'west': BoundaryCondition.Type.Reflective
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})
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# Construct simulator
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arguments = {
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'rho': rho, 'rho_u': rho * u, 'rho_v': rho * v, 'E': E,
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'nx': nx, 'ny': ny,
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'dx': dx, 'dy': dy,
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'g': g,
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'gamma': gamma,
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'boundary_conditions': bc
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}
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return arguments
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