AI Diagnostics for Inertial Fusion
Real-time anomaly detection for fusion target implosions
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9
1342
31
$140k
Project Overview
About this Research
Lawrence Livermore National Laboratory scientists are training physics-informed neural networks on terabytes of National Ignition Facility shot data. The models identify failure modes in under 200 milliseconds, giving operators the ability to adjust future shot configurations faster. USC ISI contributes scalable inference infrastructure, and all calibration data is released for the broader fusion community.
Research Milestones
Dataset release
Publish annotated implosion dataset for community benchmarking
Funding Progress
24h Change
+12.5%
Avg. Stake
$285
Velocity
High
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