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[Example] Add karman vortex street example #6249

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176 changes: 176 additions & 0 deletions python/taichi/examples/simulation/karman_vortex_street.py
Original file line number Diff line number Diff line change
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# Fluid solver based on lattice boltzmann method using taichi language
# Author : Wang (hietwll@gmail.com)
# Original code at https://github.com/hietwll/LBM_Taichi

import matplotlib
import numpy as np
from matplotlib import cm

import taichi as ti
import taichi.math as tm

ti.init(arch=ti.gpu)

vec9 = ti.types.vector(9, float)
imat9x2 = ti.types.matrix(9, 2, int)


@ti.data_oriented
class lbm_solver:
def __init__(
self,
nx, # domain size
ny,
niu, # viscosity of fluid
bc_type, # [left,top,right,bottom] boundary conditions: 0 -> Dirichlet ; 1 -> Neumann
bc_value, # if bc_type = 0, we need to specify the velocity in bc_value
cy=0, # whether to place a cylindrical obstacle
cy_para=[0.0, 0.0, 0.0], # location and radius of the cylinder
):
self.nx = nx # by convention, dx = dy = dt = 1.0 (lattice units)
self.ny = ny
self.niu = niu
self.tau = 3.0 * niu + 0.5
self.inv_tau = 1.0 / self.tau
self.rho = ti.field(float, shape=(nx, ny))
self.vel = ti.Vector.field(2, float, shape=(nx, ny))
self.mask = ti.field(float, shape=(nx, ny))
self.f_old = ti.Vector.field(9, float, shape=(nx, ny))
self.f_new = ti.Vector.field(9, float, shape=(nx, ny))
self.w = vec9(4, 1, 1, 1, 1, 1 / 4, 1 / 4, 1 / 4, 1 / 4) / 9.0
self.e = imat9x2([0, 0], [1, 0], [0, 1], [-1, 0], [0, -1], [1, 1],
[-1, 1], [-1, -1], [1, -1])
self.bc_type = ti.field(int, 4)
self.bc_type.from_numpy(np.array(bc_type, dtype=np.int32))
self.bc_value = ti.Vector.field(2, float, shape=4)
self.bc_value.from_numpy(np.array(bc_value, dtype=np.float32))
self.cy = cy
self.cy_para = tm.vec3(cy_para)

@ti.func # compute equilibrium distribution function
def f_eq(self, i, j):
eu = self.e @ self.vel[i, j]
uv = tm.dot(self.vel[i, j], self.vel[i, j])
return self.w * self.rho[i,
j] * (1 + 3 * eu + 4.5 * eu * eu - 1.5 * uv)

@ti.kernel
def init(self):
self.vel.fill(0)
self.rho.fill(1)
self.mask.fill(0)
for i, j in self.rho:
self.f_old[i, j] = self.f_new[i, j] = self.f_eq(i, j)
if self.cy == 1:
if ((i - self.cy_para[0])**2 +
(j - self.cy_para[1])**2 <= self.cy_para[2]**2):
self.mask[i, j] = 1.0

@ti.kernel
def collide_and_stream(self): # lbm core equation
for i, j in ti.ndrange((1, self.nx - 1), (1, self.ny - 1)):
for k in ti.static(range(9)):
ip = i - self.e[k, 0]
jp = j - self.e[k, 1]
feq = self.f_eq(ip, jp)
self.f_new[i, j][k] = (1 - self.inv_tau) * self.f_old[
ip, jp][k] + feq[k] * self.inv_tau

@ti.kernel
def update_macro_var(self): # compute rho u v
for i, j in ti.ndrange((1, self.nx - 1), (1, self.ny - 1)):
self.rho[i, j] = 0
self.vel[i, j] = 0, 0
for k in ti.static(range(9)):
self.f_old[i, j][k] = self.f_new[i, j][k]
self.rho[i, j] += self.f_new[i, j][k]
self.vel[i, j] += tm.vec2(self.e[k, 0],
self.e[k, 1]) * self.f_new[i, j][k]

self.vel[i, j] /= self.rho[i, j]

@ti.kernel
def apply_bc(self): # impose boundary conditions
# left and right
for j in ti.ndrange(1, self.ny - 1):
# left: dr = 0; ibc = 0; jbc = j; inb = 1; jnb = j
self.apply_bc_core(1, 0, 0, j, 1, j)

# right: dr = 2; ibc = nx-1; jbc = j; inb = nx-2; jnb = j
self.apply_bc_core(1, 2, self.nx - 1, j, self.nx - 2, j)

# top and bottom
for i in ti.ndrange(self.nx):
# top: dr = 1; ibc = i; jbc = ny-1; inb = i; jnb = ny-2
self.apply_bc_core(1, 1, i, self.ny - 1, i, self.ny - 2)

# bottom: dr = 3; ibc = i; jbc = 0; inb = i; jnb = 1
self.apply_bc_core(1, 3, i, 0, i, 1)

# cylindrical obstacle
# Note: for cuda backend, putting 'if statement' inside loops can be much faster!
for i, j in ti.ndrange(self.nx, self.ny):
if (self.cy == 1 and self.mask[i, j] == 1):
self.vel[i, j] = 0, 0 # velocity is zero at solid boundary
inb = 0
jnb = 0
if i >= self.cy_para[0]:
inb = i + 1
else:
inb = i - 1
if j >= self.cy_para[1]:
jnb = j + 1
else:
jnb = j - 1
self.apply_bc_core(0, 0, i, j, inb, jnb)

@ti.func
def apply_bc_core(self, outer, dr, ibc, jbc, inb, jnb):
if outer == 1: # handle outer boundary
if self.bc_type[dr] == 0:
self.vel[ibc, jbc] = self.bc_value[dr]

elif self.bc_type[dr] == 1:
self.vel[ibc, jbc] = self.vel[inb, jnb]

self.rho[ibc, jbc] = self.rho[inb, jnb]
self.f_old[ibc, jbc] = self.f_eq(ibc, jbc) - self.f_eq(
inb, jnb) + self.f_old[inb, jnb]

def solve(self):
gui = ti.GUI('Karman Vortex Street', (self.nx, 2 * self.ny))
self.init()
while not gui.get_event(ti.GUI.ESCAPE, ti.GUI.EXIT):
for _ in range(10):
self.collide_and_stream()
self.update_macro_var()
self.apply_bc()

## code fragment displaying vorticity is contributed by woclass
vel = self.vel.to_numpy()
ugrad = np.gradient(vel[:, :, 0])
vgrad = np.gradient(vel[:, :, 1])
vor = ugrad[1] - vgrad[0]
vel_mag = (vel[:, :, 0]**2.0 + vel[:, :, 1]**2.0)**0.5
## color map
colors = [(1, 1, 0), (0.953, 0.490, 0.016), (0, 0, 0),
(0.176, 0.976, 0.529), (0, 1, 1)]
my_cmap = matplotlib.colors.LinearSegmentedColormap.from_list(
'my_cmap', colors)
vor_img = cm.ScalarMappable(norm=matplotlib.colors.Normalize(
vmin=-0.02, vmax=0.02),
cmap=my_cmap).to_rgba(vor)
vel_img = cm.plasma(vel_mag / 0.15)
img = np.concatenate((vor_img, vel_img), axis=1)
gui.set_image(img)
gui.show()

def pass_to_py(self):
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return self.vel.to_numpy()[:, :, 0]


if __name__ == '__main__':
lbm = lbm_solver(801, 201, 0.01, [0, 0, 1, 0],
[[0.1, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]], 1,
[160.0, 100.0, 20.0])
lbm.solve()