milldem

PyPI Python License: MIT

A cross-platform soft-sphere discrete element method (DEM) engine for tumbling-mill charge motion and power. No C++ toolchain, no WSL: pure NumPy with an optional Numba JIT and an optional Torch-CUDA path. (Repo: CAOS_MillDEM; import name and PyPI dist are both milldem.)

It resolves every particle and contact with a soft-sphere contact law (linear Hookean or Hertzian, Coulomb friction, Tsuji restitution damping) and offers two routes:

  • 2D charge shape / regime (simulate, MillDEM): a fast rotating disc-slice read of the DEM charge shape (toe/shoulder) and motion regime (cascading / cataracting / centrifuging).
  • Thin-3D-slab net power (simulate_power, MillDEM3D): an axial slab with periodic axial boundaries that resolves the force chains carrying the charge lift, so the net power (van Nierop 2001 torque route, P = 2*pi*T*N) is size-consistent and within ~10% of the classical Hogg-Fuerstenau model. A single 2D disc slice cannot do this (its power/HF ratio drifts ~2x with mill size).

Install

pip install milldem              # core (numpy + scipy), runs anywhere
pip install "milldem[jit]"       # + numba, 10-50x on the hot loop
pip install "milldem[train]"     # + torch (cu126) + torch-geometric, the GPU / surrogate path

Quick start

from milldem import simulate, simulate_power, MillConfig

# 2D charge shape + regime (fast, qualitative)
m = simulate(MillConfig(diameter_m=5.0, phi_c=0.75, fill=0.30), sim_time=2.0)
print(m.regime, m.toe_deg, m.shoulder_deg)

# validated thin-3D-slab net power [kW]
p = simulate_power(MillConfig(diameter_m=5.0, phi_c=0.75, fill=0.30, ball_diameter_m=0.10), sim_time=1.5)
print(p["net_power_kw"], p["arm_m"], p["n_particles"])

CLI:

milldem run   --D 5 --phi 0.75 --J 0.30 --time 2.0 --json shape.json   # 2D charge shape / regime
milldem power --D 5 --phi 0.75 --J 0.30 --ball 0.10 --L 6.0            # validated 3D net power

Validation

See docs/VALIDATION.md for the honest validated-scope statement: verified single-particle statics, charge settling, contact-model correctness, determinism, the size-consistent thin-3D-slab power (tested in tests/test_power3d.py), and the fill handling. Nothing is fitted to hide a gap. Sources: Cundall & Strack 1979, Tsuji et al. 1992, Govender et al. 2015, van Nierop et al. 2001.

Contributing, conduct, security, license

Project links

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Credits

Author: Felipe Santibanez-Leal

GitHub Statistics

Data verified by PyPI on Jul 20, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT License (MIT)

Requires

Python >=3.10

Provides Extra

jit train dev

Tags

DEM discrete element method tumbling mill SAG ball mill comminution charge motion mineral processing

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