| Description: |
This work presents *Adaptive Resonance Control for Fusion Plasma Stability*, a study exploring resonance-driven approaches to enhance plasma confinement in magnetic fusion devices. Drawing inspiration from cymatics and biomimicry, the research applies Kuramoto oscillator networks and PDE transport models to examine entrainment dynamics and variance reduction. Key results: - Kuramoto simulations (N=100 oscillators, f■ ≈ 100 Hz) showed strong synchronization at 100 Hz (R=0.9278), with persistent coherence (τ ≈ 0.12 s). - PDE transport models (D = 10■■ m²/s, k = 0.1 s■¹) confirmed variance reduction of 15–20% and extended dwell times. - Projected MHD-level forcing predicts ~11–12% fluctuation reduction, aligning with existing DIII-D datasets. Contributions: - Establishes a cross-scale methodology for resonance-based plasma control. - Links biomimetic analogies (mitochondrial cristae folding, Oklo natural reactors) with confinement strategies. - Demonstrates how adaptive resonance control may reduce turbulence and improve confinement by 10–20%. Methodology: - Phase 1: Entrainment modeling with Kuramoto oscillators and PSD analysis. - Phase 2: PDE transport simulations for variance reduction and dwell times. - Phase 3: MHD-scale projections validated against tokamak datasets. This dataset includes the full manuscript (PDF), simulation code (Python), diagnostic outputs (CSV), and supporting dialogue logs (JSON) to ensure reproducibility. Licensed under CC BY 4.0. |