Optimisation of confinement in a fusion reactor using a nonlinear turbulence model

Abstract

The confinement of heat in the core of a magnetic fusion reactor is optimised using a multidimensional optimisation algorithm. For the first time in such a study, the loss of heat due to turbulence is modelled at every stage using first-principles nonlinear simulations which accurately capture the turbulent cascade and large-scale zonal flows. The simulations utilise a novel approach, with gyrofluid treatment of the small-scale drift waves and gyrokinetic treatment of the large-scale zonal flows. A simple near-circular equilibrium with standard parameters is chosen as the initial condition. The figure of merit, fusion power per unit volume, is calculated, and then two control parameters, the elongation and triangularity of the outer flux surface, are varied, with the algorithm seeking to optimise the chosen figure of merit. A two-fold increase in the plasma power per unit volume is achieved by moving to higher elongation and strongly negative triangularity.

32 pages, 8 figures, accepted to JPP

References in corpus (8)

• Phase mixing vs. nonlinear advection in drift-kinetic plasma turbulence
• Electromagnetic stabilization of tokamak microturbulence in a high-$\beta$ regime
• Real-time capable first principle based modelling of tokamak turbulent transport
• Laguerre-Hermite Pseudo-Spectral Velocity Formulation of Gyrokinetics
• Collisionality scaling of the electron heat flux in ETG turbulence
• Transition to subcritical turbulence in a tokamak plasma
• Suppression of phase mixing in drift-kinetic plasma turbulence
• Multiscale Gyrokinetics for Rotating Tokamak Plasmas II: Reduced Models for Electron Dynamics

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• Laguerre-Hermite Pseudo-Spectral Velocity Formulation of Gyrokinetics
• Radiative pulsed L-mode operation in ARC-class reactors
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• An adjoint method for neoclassical stellarator optimization
• An Introduction to Stellarators: From magnetic fields to symmetries and optimization
• Investigation of a Multiple-Timescale Turbulence-Transport Coupling Method in the Presence of Random Fluctuations
• Machine-learning Closure for Vlasov-Poisson Dynamics in Fourier-Hermite Space