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Fusion Plasma Modeling

topic1 events
papersSEP 12 04:00 UTC

PINN Framework Infers Perpendicular Heat Conductivity in Stellarator Scrape-Off Layer

Researchers present an inverse physics-informed neural network that estimates how the scrape-off layer's perpendicular heat conductivity varies with plasma density and temperature in stellarator devices. The approach embeds physical constraints into the learning process rather than relying solely on labeled data, allowing the conductivity function to be recovered from available measurements. This is an arXiv preprint on fusion plasma modeling and has not yet been peer reviewed.

physics/neural-networks/fusion/scientific-ml