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Physics-informed neural network

model2 events
papersTODAY 04:00 UTC

PINN framework models blood flow dynamics in abdominal aortic aneurysms

Researchers built a three-dimensional physics-informed neural network to simulate pulsatile blood flow in the human aorta, focusing on abdominal aortic aneurysm haemodynamics. The approach embeds physical laws into the training process, allowing time-resolved simulation without conventional mesh-based solvers. The work is a preprint posted to arXiv.

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 This is an arXiv preprint on fusion plasma modeling and has not yet been peer reviewed.