4 papers
Machine-learning surrogate models for nonlinear energetic-particle transport predictions in ITER
Yashika Ghai, Donald A. Spong, Jacobo Varela +1
Fast and accurate prediction of energetic-particle transport driven by Alfvén eigenmode (AE) instabilities is essential for integrated modeling workflows used in the design and opt…
Towards Data-Efficient Cross-Device Generalization of Grad-Shafranov Equilibria via Transfer Learning Neural Operator
Jay Phil Yoo, William Howes, Yashika Ghai +3
Real-time reconstruction of magnetohydrodynamic equilibria is essential for plasma shaping, stability assessment and feedback control in magnetic confinement fusion. However, Grad-…
Runaway electron interactions with whistler waves in tokamak plasmas: energy-dependent transport scaling
Yashika Ghai, D. Del-Castillo-Negrete, D. A. Spong +1
Resonant interactions between high energy runaway electrons (REs) and whistler waves are a promising mechanism for RE mitigation in tokamak plasmas. While prior studies have largel…
Exploring the Capabilities of the Frontier Large Language Models for Nuclear Energy Research
Ahmed Almeldein, Mohammed Alnaggar, Rick Archibald +47
The AI for Nuclear Energy workshop at Oak Ridge National Laboratory evaluated the potential of Large Language Models (LLMs) to accelerate fusion and fission research. Fourteen inte…