Abstract
We report on a broad study combining the capabilities of gyrokinetic codes (GENE and CGYRO) and edge fluid codes (SOLPS and UEDGE) to identify the transport mechanisms active in pedestals spanning multiple devices (DIII-D, JET, C-Mod), modes of operation (H-mode, I-mode, QH-mode), fueling / heating levels, and wall materials. The gyrokinetic codes can analyze the instabilities and transport that arise in the pedestal while the edge codes provide the best possible estimate of particle sources. This study was carried out from perspective of the so-called transport `fingerprint' conceptual framework, which compares basic physical signatures of prospective pedestal instabilities with the breadth of available experimental data, including frequency spectra, fluctuation scales and amplitudes, transport ratios, and inter-ELM profile evolution. Edge modeling determined that edge transport barriers typically lie in a regime in which heat diffusivity far exceeds particle diffusivity: De/$\chi $e $\ll $ 1, which has major implications for the role of various pedestal instabilities. In conventional ELMy H-modes, microtearing modes and ETG turbulence dominate the electron heat transport; neoclassical dominates ion heat and impurity transport; and several candidates, including KBM, remain to explain the (small) particle transport. The presence of significant ion-scale electrostatic turbulence generally results in interesting variations on the standard H-mode pedestal theme. Detailed comparisons were carried out with experimental fluctuation data. Notably, simulations of microtearing modes quantitatively match distinctive frequency bands for multiple discharges on both JET and DIII-D. This study expands our understanding the transport mechanisms that determine many important properties of edge transport barriers and lays a foundation for predicting their behavior in future devices.
* This work was supported by U.S. DOE Contract No. DE- FG02-04ER54742; U.S. DOE Office of Fusion Energy Sciences Scientific Discovery through Advanced Computing (SciDAC) program under Award Numbers DE-SC0018429 and DE- SC0018148; and General Atomics award number 4500076923. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Fusion Energy Sciences, using the DIII-D National Fusion Facility, a DOE Office of Science user facility, under Award DE-FC02-04ER54698. This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014-2018 and 2019-2020 under grant agreement No 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission.