PyFracVAL

PyFracVAL generates three-dimensional fractal-like aggregates of mono- and polydisperse primary particles using a particle-cluster/cluster-cluster aggregation (PCA/CCA) strategy. The implementation follows the FracVAL algorithm [Morán et al., 2019], with morphology conventions drawn from [Filippov et al., 2000].

Contents:

• Installation
  • Requirements
  • Development environment
  • Without devenv
  • Verifying the installation
• Usage
  • Command-line interface
  • Library usage
• Knowledge Base
  • Pipeline Baseline: Status of Stages and Variants
  • Comparison of CCA Sticking Methods
  • Cluster Pairing and Geometric Frustration in CCA Sticking
  • Matching-Based CCA Pairing: a Negative Result
  • Backtracking CCA Pairing
  • Statistical Overlap-Failure Census
  • Drop-a-Few-Particles Rescue
  • Catalog Overlap Leak: success=True Clusters With Severe Residual Overlap
  • Df/kf/σ Stability Boundary Near the Hard Regime
  • Stability Boundary After Backtracking (Sweep v2)
  • Structural Validation via the Correlation Function f(r)
  • Predicting the Feasibility Boundary
  • Profiling and Performance
  • Failure Statistics: the Structured Event Log
  • Full-Grid Stability Sweep and Runtime Model
  • GPU Acceleration Evaluation: JAX vs. Numba
• References
• API Reference
  • pyfracval