In order to understand the dependence of turbulence on flux surface shape, a study of the 3D spectrum of potential fluctuations from gyrokinetic turbulence computed with the CGYRO code was undertaken. The findings have been accepted for publication in Plasma Phys. Control. Fusion http://iopscience.iop.org/article/10.1088/1361-6587/abc861. It was found that the poloidal variation of the peak fluctuation intensity could be modeled by geometric factors present in the metric coefficients of the poloidal and radial wavenumbers. The elongation and Shafranov shift were varied in order to determine the geometric dependence of the width of the radial wavenumber spectrum and the peak amplitude of the potential spectrum as a function of the poloidal wavenumber. The width of the zonal (axisymmetric) potential fluctuation spectrum was found to set a minimum width for the rest of the spectrum controlling the net fluxes. A model of the 3D spectrum that gives a highly accurate quasi-linear flux model has been incorporated as an option in the TGLF transport model.

A GA theory team led by Emily Belli, along with Jeff Candy, Gary Staebler, and George Fann from ORNL, has received a 2021 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) Award for their proposal “Multi-Ion Turbulence in Burning Plasma Experiments“. The award allocation consists of 450,000 node-hours on Summit, the fastest supercomputer in the US, based at the Oak Ridge Leadership Computing Facility. The team will use the CGYRO code to perform “capability computing” simulations to model energy and particle losses due to turbulent transport in burning plasma scenarios and develop an understanding of how complex multi-ion interactions between D and T fuel ions, fusion helium ash, wall impurities (beryllium and tungsten), and electrons affect plasma performance. The CGYRO algorithm has been highly optimized for scalability on advanced HPC systems like Summit that use multicore and GPU-accelerator hardware. These simulations will make optimal use of the leadership-scale multi-species and multiscale plasma turbulence simulation capabilities of CGYRO in understanding burning plasmas in preparation for ITER.

Three invited talks were presented (remotely) at the APS Division of Plasma Physics conference this week:

Emily Belli presented an invited talk on “Strong Reversal of Simple Isotope Scaling Laws in Tokamak Edge Turbulence”

Valerie Izzo presented an invited talk on “MHD modeling of dispersive shell-pellet injection as an alternative disruption-mitigation technique”

Xiang Jian presented an invited talk on “Destabilization of High-Field-Side Micro-Instabilities by Large Shafranov Shift in Present and Future Devices”

Emily Belli’s research was also described in an APS press release “Turbulent Relationship: Understanding the Mysterious Hydrogen 'Isotope Effect' in Fusion Experiments” (see https://www.aps.org/newsroom/vpr/dpp/2020/11-09-2020-01.cfm)

In addition, Valerie Izzo’s research, together with that of Robert Wilcox, was described in an APS press release:
“Taming Fusion Plasmas with Ice Cubes and Diamond Shells” (see https://www.aps.org/newsroom/vpr/dpp/2020/11-09-2020-05.cfm)

A big data approach to validating tokamak transport models will be reported by Tom Neiser (ORISE) at the APS-DPP meeting next week. A database of 80000 time and space points was constructed from 2500 randomly selected plasma discharges in DIII-D. A set of good data selection filters was then applied to curate the dataset. The quasi-linear transport model TGLF was then successfully tested against this curated dataset. Machine learning tools are being used to identify any promising areas of improvement for the model.