Beispiel #1
0
import scipy.spatial
from PyGran import Analyzer
from numpy import arange, array
import os

Gran = Analyzer.System(Particles='traj.dump')

# Go to last frame
Gran.goto(-1)

# Create a new class containing particles between  z=0 and z=1e-3
Particles = Gran.Particles
Particles = Particles[Particles.z <= 1e-3 & Particles.z >= 0]

# Set image resolution and size
resol = 1.24e-6 # microns/pixel
size = (512, 512)

for i, z in enumerate(arange(0, Particles.z.max() + resol, resol)):
	zmin, zmax = z, z + resol
	output =  'output/poured{}.bmp'.format(i))
	Analyzer.imaging.slice(Particles, zmin, zmax, 'z', size, resol, output)
Beispiel #2
0
    c = reff * sqrt(gamma * pi / (2.0 * YoungEff))

    # Solve the algebraic equation symbolically
    frac = 0.333333333333333333333333333333333333333333333333333
    common = (9 * c + sqrt(3 * (27 * c**2 - 4 * b**3)))**frac

    x = b * (2.0 / 3.0)**frac / common + common / (18**frac)

    # Compute contact yield radius
    ay = x * x

    # Return yielding contact radius
    return ay * ay / reff - sqrt(2.0 * pi * gamma * ay / YoungEff)


System = Analyzer.System("traj-tapping.dump")
data = []

for ts in System:
    Neigh = Analyzer.Neighbors(System.Particles)
    overlaps, indices = Neigh.overlaps[:, 0], Neigh.overlaps[:, 1:]

    # Extract radii of all particles
    radii = System.Particles.radius

    ny = 0

    for contact, index in enumerate(indices):

        # Get the two particle (in contact) indices
        i, j = index
Beispiel #3
0
natoms = 10
radius = 1

data['natoms'] = natoms * natoms * natoms
data['id'] = arange(data['natoms'])

data['x'], data['y'], data['z'] = zeros(data['natoms']), zeros(
    data['natoms']), zeros(data['natoms'])

data['id'] = arange(data['natoms'])
count = 0
for i in range(natoms):
    for j in range(natoms):
        for k in range(natoms):
            data['x'][count] = (2.0 * i + ((j + k) % 2)) * radius
            data['y'][count] = (sqrt(3.) * (j + 1.0 / 3.0 * (k % 2))) * radius
            data['z'][count] = (2.0 * sqrt(6.0) / 3.0 * k) * radius
            count += 1

data['radius'] = ones(data['natoms']) * radius
data['timestep'] = 0
data['box'] = ([data['x'].min(),
                data['x'].max()], [data['y'].min(), data['y'].max()],
               [data['z'].min(), data['z'].max()])

Particles = Analyzer.Particles(data=data, units='micro')

System = Analyzer.System(Particles=Particles)
System.Particles.write('hpc.dump')
print System.Particles.density(1)
Beispiel #4
0
	c = reff * sqrt(gamma * pi / (2. * YoungEff))

	# Solve the algebraic equation symbolically
	frac = 0.333333333333333333333333333333333333333333333333333	
	common = (9*c + sqrt(3*(27*c**2 - 4*b**3)))**frac

	x = b * (2.0/3.0)**frac /  common + common / (18**frac)

	# Compute contact yield radius
	ay = x*x

	# Return yielding contact radius
	return ay*ay/reff - sqrt(2. * pi * gamma * ay / YoungEff)


System = Analyzer.System('/run/media/abimanso/Disk-2/Papers/DEM-XRCT/Sim-Data/Stearic-acid/Tapping/traj/traj-tapping.dump')
data = []

for ts in System:
	Neigh = Analyzer.Neighbors(System.Particles)
	overlaps, indices = Neigh.overlaps[:,0], Neigh.overlaps[:,1:]

	# Extract radii of all particles
	radii = System.Particles.radius

	ny = 0

	for contact, index in enumerate(indices):

		# Get the two particle (in contact) indices
		i,j = index
Beispiel #5
0
from PyGran import Analyzer
import matplotlib.pylab as plt
from numpy import array

# Create a PyGran System from a dump file (default si units)
System = Analyzer.System(Particles='/home/levnon/Desktop/flow/output/traj/traj*.dump')

# Timestep used in simulation (s)
dt = 1e-6

# Skip empty frames
System.skip()

# Extract bed height + timesteps
data = array([[ts * dt,System.Particles.z.max()] for ts in System])

# Plot bed height (mm) vs time (ms)
plt.plot(data[:,0] * 1e3, data[:,1] * 1e3, '-o')

plt.xlabel('Time (ms)')
plt.ylabel('Height (mm)')
plt.grid(linestyle=':')
plt.show()
Beispiel #6
0
from PyGran import Analyzer
from PyGran.Materials import glass

System = Analyzer.System('traj.dump')
System.goto(-1)

Neigh = Analyzer.Neighbors(System.Particles)
overlaps, i, j = Neigh.overlaps

print Neigh.filter()