38 citations · 86 across the 7 of their papers we have counts for
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A Physics-Informed Deep Learning Description of Knudsen Layer Reactivity Reduction
Christopher J. McDevitt, Xian-Zhu Tang
A physics-informed neural network (PINN) is used to evaluate the fast ion distribution in the hot spot of an inertial confinement fusion target. The use of tailored input and outpu…
A Physics-Informed Deep Learning Model of the Hot Tail Runaway Electron Seed
Christopher McDevitt
A challenging aspect of the description of a tokamak disruption is evaluating the hot tail runaway electron (RE) seed that emerges during the thermal quench. This problem is made c…
Runaway electron current reconstitution after a non-axisymmetric magnetohydrodynamic flush
Christopher J. McDevitt, Xian-Zhu Tang
Benign termination of mega-ampere (MA) level runaway current has been convincingly demonstrated in recent JET and DIII-D experiments, establishing it as a leading candidate for run…
The constraint of plasma power balance on runaway avoidance
Christopher J. McDevitt, Xian-Zhu Tang, Christopher J. Fontes +2
In a post-thermal-quench plasma, mitigated or unmitigated, the plasma power balance is mostly between collisional or Ohmic heating and plasma radiative cooling. In a plasma of atom…
Impact of a minority relativistic electron tail interacting with a thermal plasma containing high-atomic-number impurities
Nathan A. Garland, Hyun-Kyung Chung, Christopher J. Fontes +6
A minority relativistic electron component can arise in both laboratory and naturally-occurring plasmas. In the presence of high-atomic-number ion species, the ion charge state dis…
Self-similar structure and experimental signatures of suprathermal ion distribution in inertial confinement fusion implosions
Grigory Kagan, D. Svyatskiy, H. G. Rinderknecht +4
The distribution function of suprathermal ions is found to be self-similar under conditions relevant to inertial confinement fusion hot-spots. By utilizing this feature, interferen…