28 citations · 28 across the 2 of their papers we have counts for
5 papers
Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks
J. Zhu, C. Rea, R. S. Granetz +10
Next generation high performance (HP) tokamaks risk damage from unmitigated disruptions at high current and power. Achieving reliable disruption prediction for a device's HP operat…
Hybrid deep learning architecture for general disruption prediction across tokamaks
J. X. Zhu, C. Rea, K. Montes +3
In this paper, we present a new deep learning disruption prediction algorithm based on important findings from explorative data analysis which effectively allows knowledge transfer…
An application of survival analysis to disruption prediction via Random Forests
R. A. Tinguely, K. J. Montes, C. Rea +2
One of the most pressing challenges facing the fusion community is adequately mitigating or, even better, avoiding disruptions of tokamak plasmas. However, before this can be done,…
Neutron diagnostics for the physics of a high-field, compact, tokamak
R. A. Tinguely, A. Rosenthal, R. Simpson +18
Advancements in high temperature superconducting technology have opened a path toward high-field, compact fusion devices. This new parameter space introduces both opportunities and…
Conceptual design study for heat exhaust management in the ARC fusion pilot plant
A. Q. Kuang, N. M. Cao, A. J. Creely +13
The ARC pilot plant conceptual design study has been extended beyond its initial scope [B. N. Sorbom et al., FED 100 (2015) 378] to explore options for managing ~525 MW of fusion p…