2D Grain Structure Generation

2D Grain Structure Generation

UPXO supports two primary methods for generating 2D polycrystalline grain structures.

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Monte Carlo Grain Structure (MCGS2D)

MCGS2D uses the Potts model Monte Carlo algorithm to simulate grain growth from a random initial state. The simulation is driven by an Excel dashboard (gschar1.xls) which exposes all key parameters.

Key parameters:

• Grid size (nx, ny)
• Number of grain orientations (Q)
• Number of Monte Carlo steps (MCS)
• Temperature (kT)
• Sampling intervals (time slices)

Entry point: src/upxo/demos/gschar/gschar1.ipynb

Custom algorithms: You can supply your own growth rate function by subclassing the MC engine. See the ggrowth/mcgs.py module and algorithms/ for reference implementations.

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Voronoi Tessellation (VTGS2D)

Voronoi-based 2D grain structures are generated from a set of seed points using pyvoro. Grain morphology is controlled by seed point distribution and domain geometry.

Entry point: src/upxo/pxtal/vortess2d.py

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Coming Soon

• Detailed parameter sweeping guide (parswep/mcgs2d_parameter_sweeping.py)
• Gradient grain structure generation
• Spatial grain size distribution control