Waste Loading Optimization with ML and UQ for Hanford Vitrification
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YouTubeAPMonitor.com
Waste Loading Optimization with ML and UQ for Hanford Vitrification
In this PhD dissertation defense, LaGrande Gunnell presents research on improving Hanford nuclear waste vitrification algorithms through advanced computational methods. The work specifically focuses on integrating machine learning (ML), uncertainty quantification (UQ), and gradient-based optimization techniques to optimize nuclear waste glass ...
736 viewsMar 20, 2025
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