def __init__(self, cells, gas, domain, surf_group,n_par_in_cell,
dt, n_steps, Detector, Collider, Reflector,
ignore_frac=0.1, multiphase=False):
self.n_steps = n_steps
self.cells = cells
self.open = domain.is_open()
self.particles, self.cells_in = Initialiser.run(cells, gas, surf_group,
domain, n_par_in_cell,
not self.open, multiphase)
self.collision_manager = CollisionManager(cells, self.particles, gas,
dt, Detector, Collider)
self.sampling_manager = SamplingManager(cells, self.cells_in,
gas.get_n_species(), self.particles,
n_steps, ignore_frac)
self.movement_manager = MovementManager(self.particles, surf_group,
Reflector)
self.dt = dt
self.temperature = np.zeros(len(cells.get_temperature()))
self.number_density = np.zeros((gas.get_n_species(),
len(cells.get_temperature())))
if (self.open):
self.boundary_manager = dm_b.BoundaryManager(cells, domain, gas,
self.particles, n_par_in_cell)
self.boundary_manager.run([], self.dt)
def __init__(self):
self.movement_manager = MovementManager()
self.is_collecting = False
self.previous_command = self.INITIAL_CMD
class DsmcSolver:
def __init__(self, cells, gas, domain, surf_group,n_par_in_cell,
dt, n_steps, Detector, Collider, Reflector,
ignore_frac=0.1, multiphase=False):
self.n_steps = n_steps
self.cells = cells
self.open = domain.is_open()
self.particles, self.cells_in = Initialiser.run(cells, gas, surf_group,
domain, n_par_in_cell,
not self.open, multiphase)
self.collision_manager = CollisionManager(cells, self.particles, gas,
dt, Detector, Collider)
self.sampling_manager = SamplingManager(cells, self.cells_in,
gas.get_n_species(), self.particles,
n_steps, ignore_frac)
self.movement_manager = MovementManager(self.particles, surf_group,
Reflector)
self.dt = dt
self.temperature = np.zeros(len(cells.get_temperature()))
self.number_density = np.zeros((gas.get_n_species(),
len(cells.get_temperature())))
if (self.open):
self.boundary_manager = dm_b.BoundaryManager(cells, domain, gas,
self.particles, n_par_in_cell)
self.boundary_manager.run([], self.dt)
def run(self):
move_time = 0.0
dist_time = 0.0
col_time = 0.0
samp_time = 0.0
bound_time = 0.0
for i in range(self.n_steps):
print "time_sample = ", i, " ",
start = time.time()
self.movement_manager.move_all(self.dt)
move_time += time.time() - start
start = time.time()
self.cells.distribute_all_particles(self.particles)
dist_time += time.time() - start
start = time.time()
self.collision_manager.collide()
col_time += time.time() - start
start = time.time()
self.sampling_manager.sample()
samp_time += time.time() - start
if (self.open):
start = time.time()
particles_out = self.cells.get_particles_out()
# print "length of particles out = ", len(particles_out)
self.boundary_manager.run(particles_out, self.dt)
bound_time += time.time() - start
print "movement time = ", move_time
print "distribution time = ", dist_time
print "collisio time = ", col_time
print "sampling time = ", samp_time
print "bound_time = ", bound_time
def _find_moving_particles(self, reflected_particles):
index_list = range(self.particles.get_particles_count())
for index in reflected_particles:
np.delete(index_list, index)
return index_list
# this function should return temperature in 2d numpy array
def get_2d_temperature(self, cell_x, cell_y):
return self._convert_to_2d(cell_x, cell_y,
self.sampling_manager.get_temperature())
# this function should return mach in 2d numpy array
def get_2d_speed(self, cell_x, cell_y):
return self._convert_to_2d(cell_x, cell_y,
self.sampling_manager.get_speed())
# this function should return mach in 2d numpy array
def get_2d_u(self, cell_x, cell_y):
return self._convert_to_2d(cell_x, cell_y,
self.sampling_manager.get_u())
# this function should return mach in 2d numpy array
def get_2d_v(self, cell_x, cell_y):
return self._convert_to_2d(cell_x, cell_y,
self.sampling_manager.get_v())
# this function should return mach in 2d numpy array
def get_2d_w(self, cell_x, cell_y):
return self._convert_to_2d(cell_x, cell_y,
self.sampling_manager.get_w())
# this function should return number density in 2d numpy array
def get_2d_num_den(self, cell_x, cell_y, tag=0):
return self._convert_to_2d(cell_x, cell_y,
self.sampling_manager.get_number_density(tag))
# this function should convert 1d numpy array to 2d numpy array given
# x dimension and y dimension.
def _convert_to_2d(self, cell_x, cell_y, array):
cell_x, cell_y = int(cell_x), int(cell_y)
new_array = np.zeros((cell_y, cell_x), dtype=float)
for i in range(cell_x):
for j in range(cell_y):
new_array[i][j] = array[j * cell_x + i]
return new_array
