
A comprehensive tokamak plasma physics simulation and control suite with 54 Python modules, 10 Rust crates, 26 simulation modes, and a neuro-symbolic Petri net to stochastic neuron compiler. Features Grad-Shafranov equilibrium, MHD stability, transport, RF heating, neutronics, disruption prediction, and the MVR-0.96 compact reactor optimizer with optional SC-NeuroCore SNN integration.
Part of the SCPN (Self-Consistent Phenomenological Network) research framework by ANULUM. Published on Zenodo and Academia.edu.
fusion, Grad-Shafranov, plasma physics, MHD, digital twin, spiking neural networks, neuro-symbolic, reactor design, tokamak, SCPN
fusion, Grad-Shafranov, plasma physics, MHD, digital twin, spiking neural networks, neuro-symbolic, reactor design, tokamak, SCPN
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