FIREFLY offers simplified approximations for divertor heat loads and particle exhaust to speed up design evaluation in magnetic confinement fusion.
Performance of different tungsten grades under transient thermal loads
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
fields
physics.plasm-ph 4years
2026 4verdicts
UNVERDICTED 4representative citing papers
A materials-limited HTS tokamak design achieves net electricity for off-grid uses at 130 MW fusion power with self-consistent high-field plasma parameters and detached divertor operation.
SOLPS-NN is a fully connected neural network surrogate trained on SOLPS-ITER simulations that predicts spatial plasma profiles and indicates access to detachment with experimental trends.
The MPEX AI Digital Twins project reports that its two phase-I AI milestones for hot-spot control and damage assessment are on track for June 2026 demonstration.
citing papers explorer
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FIREFLY: heat load and particle exhaust approximations for rapid evaluation of divertor designs
FIREFLY offers simplified approximations for divertor heat loads and particle exhaust to speed up design evaluation in magnetic confinement fusion.
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Yinsen: A low power density HTS tokamak fusion reactor for marine and off-grid applications
A materials-limited HTS tokamak design achieves net electricity for off-grid uses at 130 MW fusion power with self-consistent high-field plasma parameters and detached divertor operation.
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Deep-Learning based surrogate models for plasma exhaust simulations -- SOLPS-NN
SOLPS-NN is a fully connected neural network surrogate trained on SOLPS-ITER simulations that predicts spatial plasma profiles and indicates access to detachment with experimental trends.
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MPEX AI Digital Twins Milestone Report
The MPEX AI Digital Twins project reports that its two phase-I AI milestones for hot-spot control and damage assessment are on track for June 2026 demonstration.