Skip to content
/ bola Public

Collection of sphere packing and meshing algorithms.

License

Notifications You must be signed in to change notification settings

TTitscher/bola

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

13 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation


Collection of sphere packing and meshing algorithms.

Installation

pip3 install bola

The c++ code requires the math library Eigen3 to be installed and a dependency of the python gmsh package is libglu. So, you may need to run (debian/ubuntu-based):

sudo apt update
sudo apt -y install libeigen3-dev libglu1

Alternatively, you can follow the steps of the CI.

Examples

Particle size according to bola.psd.GradingCurve (sieve lines):

gc = bola.psd.GradingCurves.fuller(d_min=4., d_max=16)
box = (32.0, 32.0, 32.0)
radii = psd.sample_grading_curve(gc, V=0.5 * np.prod(box))


Initial packing using bola.packing.rsa (random sequential addition)

spheres = bola.packing.rsa(radii, box)


Maximize particle distance using bola.packing.edmd (event-driven molecular-dynamics)

sim = bola.packing.edmd(box, spheres, growth_rate=0.1)
while sim.t() < 10.0:
    sim.process(100 * len(radii))
    sim.synchronize(True)
    print(packing.stats_string(sim))
distant_spheres = sim.spheres()
distant_spheres[:, 3] = radii # new centers, old radii


Mesh via gmsh using bola.mesh

bola.mesh.create(
    box, new_spheres, bola.mesh.GmshOptions(
        mesh_size_matrix=2.0, mesh_size_aggregates=2.0, out="mesh.xdmf")
)