Author: Brendan C Lyons
Requested Type: Pre-Selected Invited
Submitted: 2017-03-17 16:59:54
Co-authors: L. Cui, T.E. Evans, N.M. Ferraro, L.L. Lao, N.C. Logan, O. Meneghini, C. Paz-Soldan, S.P. Smith, P.B. Snyder
P.O. Box 85608
San Diego, California 92186-5
As the use of 3D magnetic perturbations has become widespread in tokamaks (e.g., edge-localized mode [ELM] suppression), theoretical insight into the plasma response to these fields has become essential. Efficient magnetohydrodynamics (MHD) modeling is required in order to understand past experiments, to guide ongoing or future experiments, and to quantify the sensitivity of simulation results to uncertainties in equilibrium reconstruction, measured plasma parameters, and model assumptions. To facilitate such studies, a new Python utility, autoC1, has been developed to automate running the M3D-C1 extended-MHD code  for linear simulations. In addition, we have incorporated autoC1 into the OMFIT framework , allowing for the creation of advanced integrated-modeling workflows with extended-MHD analysis. After introducing these capabilities, we present results from two workflows enabled by these tools. The first involves computing kinetic equilibrium reconstructions for the DIII-D tokamak and using autoC1 to compute the plasma response, all on the run day of an ELM-suppression experiment. The second couples autoC1 to EFIT  in order to perform a numerical scan of triangularity and its effect on 3D plasma response. In addition, we couple EPED  to this workflow to explore how self-consistent modifications to the pressure and current profiles caused by the shape change impact the plasma response. This study forms the basis of a predict-first analysis for upcoming triangularity scan experiments on DIII-D, ASDEX Upgrade, and KSTAR.
Work supported by US DOE grant nos DE-FG02-95ER54309, DE-FC02-06ER54873, DE-FC02-04ER54698, & DE-SC0015499, and the National Fusion Research Institute, South Korea.