Conceptual design study for heat exhaust management in the ARC fusion pilot plant

Uncovering turbulent plasma dynamics via deep learning from partial observations

One of the most intensely studied aspects of magnetic confinement fusion is edge plasma turbulence which is critical to reactor performance and operation. Drift-reduced Braginskii two-fluid theory has for decades been widely applied to model boundary plasmas with varying success. Towards better understanding edge turbulence in both theory and experiment, we demonstrate that a physics-informed deep learning framework constrained by partial differential equations can accurately learn turbulent fields consistent with the two-fluid theory from partial observations of electron pressure which is not otherwise possible using conventional equilibrium models. This technique presents a paradigm for the advanced design of plasma diagnostics and validation of magnetized plasma turbulence theories in challenging thermonuclear environments.

Small, modular and economically attractive fusion enabled by high temperature superconductors

The advantages of high magnetic fields in tokamaks are reviewed, and why they are important in leading to more compact tokamaks. A brief explanation is given of what limits the magnetic field in a tokamak, and why high temperature superconductors (HTSs) are a game changer, not just because of their higher magnetic fields but also for reasons of higher current density and higher operating temperatures. An accelerated pathway to fusion energy is described, defined by the SPARC and ARC tokamak designs. This article is part of a discussion meeting issue 'Fusion energy using tokamaks: can development be accelerated?'.