Turbulence is a major obstacle for building fusion reactors. We use theory and simulation to further our understanding of turbulence and ultimately find magnetic field shapes that minimise turbulence.

Thanks to the multitude of shapes available, we can optimise stellarators even for turbulence.

Plasma turbulence is one of the last fundamental obstacles to harnessing nuclear fusion for power generation. The stellarator concept, which is presently seeing the successful operation of the Wendelstein 7-X experiment, can potentially be optimized to make turbulence negligible. However, in W7-X the magnetic field geometry is optimized for good confinement only. Due to the computational expense of direct numerical turbulence simulation in 3D stellarator geometry, and the lack of accurate reduced predictive models, turbulence could not be incorporated in the optimisation of the design. But it must, if the stellarator concept is to be a power plant candidate. 

We aim at building a framework for turbulence optimisation in stellarators. The key enabling component is a reduced turbulence model sufficiently tractable to incorporate into an optimisation process. This demands understanding both the underlying instabilities as well as the saturation mechanisms by which the underlying linear instabilities nonlinearly couple to define the turbulent state.

By means of analytical calculations, simulations using the advanced gyrokinetics code GENE and comparisons with experiments performed on W7-X, we study and classify the different saturation mechanisms available, and model how both drive and saturation depend on the magnetic geometry. 

Ultimately, our aim is to build an accurate turbulence model allowing for fast simulations of turbulence-driven heat loss. In that way we can explore the large stellarator design-space and tailor a low-turbulence confinement regime.