def create_particles(self):
hcp = self.options.hcp
# Initial distribution using Hexagonal close packing of particles
# create all particles
global dx
if hcp:
x, y, dx, dy, xmin, xmax, ymin, ymax = uniform_distribution.uniform_distribution_hcp2D(
dx=dx,
xmin=-ghost_extent,
xmax=Lx + ghost_extent,
ymin=-ghost_extent,
ymax=Ly + ghost_extent)
else:
x, y, dx, dy, xmin, xmax, ymin, ymax = uniform_distribution.uniform_distribution_cubic2D(
dx=dx,
xmin=-ghost_extent,
xmax=Lx + ghost_extent,
ymin=-ghost_extent,
ymax=Ly + ghost_extent)
x = x.ravel()
y = y.ravel()
# create the basic particle array
solid = get_particle_array(name='solid', x=x, y=y)
# now sort out the interior from all particles
indices = _get_interior(solid.x, solid.y)
fluid = solid.extract_particles(indices)
fluid.set_name('fluid')
solid.remove_particles(indices)
# sort out the obstacle from the interior
indices = _get_obstacle(fluid.x, fluid.y)
obstacle = fluid.extract_particles(indices)
obstacle.set_name('obstacle')
fluid.remove_particles(indices)
print(
"SPHERIC benchmark 6 :: Re = %d, nfluid = %d, nsolid=%d, nobstacle = %d, dt = %g"
% (Re, fluid.get_number_of_particles(),
solid.get_number_of_particles(),
obstacle.get_number_of_particles(), dt))
# setup requisite particle properties and initial conditions
if hcp:
wij_sum = uniform_distribution.get_number_density_hcp(
dx, dy, kernel, h0)
volume = 1. / wij_sum
else:
volume = dx * dy
particles = self._setup_particle_properties([fluid, solid, obstacle],
volume=volume)
return particles
def create_particles(hcp=False, **kwargs):
"Initial distribution using Hexagonal close packing of particles"
# create all particles
global dx
if hcp:
x, y, dx, dy, xmin, xmax, ymin, ymax = uniform_distribution.uniform_distribution_hcp2D(
dx=dx, xmin=-ghost_extent, xmax=Lx+ghost_extent,
ymin=-ghost_extent, ymax=Ly+ghost_extent)
else:
x, y, dx, dy, xmin, xmax, ymin, ymax = uniform_distribution.uniform_distribution_cubic2D(
dx=dx, xmin=-ghost_extent, xmax=Lx+ghost_extent,
ymin=-ghost_extent, ymax=Ly+ghost_extent)
x = x.ravel(); y = y.ravel()
# create the basic particle array
solid = get_particle_array(name='solid', x=x, y=y)
# now sort out the interior from all particles
indices = _get_interior(solid.x, solid.y)
fluid = solid.extract_particles( indices )
fluid.set_name('fluid')
solid.remove_particles( indices )
# sort out the obstacle from the interior
indices = _get_obstacle(fluid.x, fluid.y)
obstacle = fluid.extract_particles( indices )
obstacle.set_name('obstacle')
fluid.remove_particles(indices)
print "SPHERIC benchmark 6 :: Re = %d, nfluid = %d, nsolid=%d, nobstacle = %d, dt = %g"%(
Re, fluid.get_number_of_particles(),
solid.get_number_of_particles(),
obstacle.get_number_of_particles(), dt)
# setup requisite particle properties and initial conditions
if hcp:
wij_sum = uniform_distribution.get_number_density_hcp(dx, dy, kernel, h0)
volume = 1./wij_sum
else:
volume = dx*dy
particles = _setup_particle_properties([fluid, solid, obstacle], volume=volume)
return particles
# Uniform hexagonal close packing arrangement of particles
#x, y, dx, dy, xmin, xmax, ymin, ymax = uniform_distribution_hcp2D(
# dx, xmin=0.0, xmax=1., ymin=0.0, ymax=1., adjust=True)
# SPH kernel
#k = CubicSpline(dim=2)
#k = Gaussian(dim=2)
#k = QuinticSpline(dim=2)
k = WendlandQuintic(dim=2)
# for the hexagonal particle spacing, dx*dy is only an approximate
# expression for the particle volume. As far as the summation density
# test is concerned, the value will be uniform but not equal to 1. To
# reproduce a density profile of 1, we need to estimate the kernel sum
# or number density of the distribution based on the kernel
wij_sum_estimate = get_number_density_hcp(dx, dy, k, h0)
volume = 1./wij_sum_estimate
print 'Volume estimates :: dx^2 = %g, Number density = %g'%(dx*dy, volume)
x = x.ravel(); y = y.ravel()
h = numpy.ones_like(x) * h0
m = numpy.ones_like(x) * volume
wij = numpy.zeros_like(x)
# use the helper function get_particle_array to create a ParticleArray
pa = utils.get_particle_array(x=x,y=y,h=h,m=m,wij=wij)
# the simulation domain used to request periodicity
domain = DomainManager(
xmin=min, xmax=max, ymin=min, ymax=max,periodic_in_x=False, periodic_in_y=False)
ymin=0.0,
ymax=1.0,
adjust=True)
# SPH kernel
#k = CubicSpline(dim=2)
#k = Gaussian(dim=2)
#k = QuinticSpline(dim=2)
k = WendlandQuintic(dim=2)
# for the hexagonal particle spacing, dx*dy is only an approximate
# expression for the particle volume. As far as the summation density
# test is concerned, the value will be uniform but not equal to 1. To
# reproduce a density profile of 1, we need to estimate the kernel sum
# or number density of the distribution based on the kernel
wij_sum_estimate = get_number_density_hcp(dx, dy, k, h0)
volume = 1. / wij_sum_estimate
print('Volume estimates :: dx^2 = %g, Number density = %g' % (dx * dy, volume))
x = x.ravel()
y = y.ravel()
h = numpy.ones_like(x) * h0
m = numpy.ones_like(x) * volume
wij = numpy.zeros_like(x)
# use the helper function get_particle_array to create a ParticleArray
pa = utils.get_particle_array(x=x, y=y, h=h, m=m, wij=wij)
# the simulation domain used to request periodicity
domain = DomainManager(xmin=0.,
xmax=1.,
