Hot tail runaway electron production is extremely sensitive to the initial electric field, and thus the plasma electrical conductivity, and the neoclassical correction, must be accounted for. A key ingredient in the neoclassical correction is the fraction of circulating electrons, f_c, in the collisionless regime, which involves an evaluation of two nested integrals that are difficult to calculate for arbitrary equilibria. An economical fitting expression was developed for the case of concentric, elliptical flux surfaces. It was found that this is adequate to describe low-beta up-down symmetric equilibria of arbitrary aspect ratio. The formula has only four adjustable coefficients and agrees with neoclassical numerical evaluation of f_c to an accuracy better than 0.01 % over the entire range of inverse aspect ratios 0 < r/R < 0.4. The formula appears to be remarkably versatile for any plasma shape; we found that without having to change any of the four coefficients used in the elliptical equilibria, a simple rescaling of the aspect ratio was able to give agreement within 3% of the f_c values that were calculated numerically in the 1995 paper by Lin-Liu and Miller for a sample high-triangularity, high-beta poloidal DIII-D experimental equilibria.

Over its long software development history, the fusion community has seen a proliferation of highly specialized numerical formats for storing the data of physics codes and experimental analyses. For many of these, the lack of standalone official numerical libraries has pushed individual researchers to develop their own set of routines to interface with such data. A centerpiece feature of the OMFIT framework are the Python classes used to interpret, manipulate, plot, and update over 100 of these data formats. These are routines that have been developed by many tens of researchers, and have been constantly used and tested by several hundreds of users on very diverse data. Recently, the OMFIT source code has been refactored to allow scientists to take advantage of these classes independently of the other functionalities and physics modules that the OMFIT framework provides. The classes are now available on the Python Package Index (PyPI) repository. This makes it easy for fusion software developers to include them within their own Python workflows and physics codes, as well as in interactive analyses within iPython and Jupyter notebooks. This is an important and necessary step to further establish the OMFIT classes as a tested and trusted standard for working with fusion data formats in Python. More details can be found at https://omfit.io/classes.html.

A new theory-based reconstruction workflow, MPMAG, has been developed for predicting MHD equilibria without having experimental profiles in hand. This predict first approach utilizes predictions of the pressure profile based on the coupled TGLF turbulent transport and EPED1 pedestal models, together with external magnetic data to construct the equilibrium. In a test using a database of 10 conventional NBI heated H-modes with monotonic q-profiles comprising of scans in plasma current, toroidal magnetic field, and triangularity, the results compare favorably against kinetic EFIT reconstruction results. The axis safety factor q₀ was not constrained in these equilibria and ranged between 0.8 and 1.4. While this comparison took advantage of magnetics data, the workflow can be invoked without it. The workflow is expected to have wide applications in experimental planning, between-shot analysis, and reactor studies. The workflow takes less than a minute on a local workstation.

The SciDAC Center for Tokamak Transient Simulation (CTTS) held a virtual code camp the week of August 3rd, 2020, attended by scientists from General Atomics, SLS2 Consulting, PPPL, and Stony Brook University. The goal was to advance the coupling of the 3D, nonlinear, extended-magnetohydrodynamics (MHD) codes M3D-C1 and NIMROD to a Lagrangian-particle (LP) code that performs detailed, local calculations of pellet ablation. The coupled codes will permit sophisticated, high-fidelity simulations of disruption mitigation by shattered-pellet injection (SPI) of cryogenic deuterium and neon. A data format was finalized for exchanging information about the pellet-ablation cloud to the MHD codes. In addition, a plan was developed to perform predictor-corrector simulations using loose coupling between the codes. MHD calculations will be performed for H-mode and Super-H-mode DIII-D plasmas of the injection of a small neon pellet, first using an analytic model for pellet ablation developed by Paul Parks. The density, temperature, and magnetic field from those simulations will be passed to the LP code, and new ablation rates will be precomputed for use in subsequent MHD calculations. The MHD codes and LP code can then be iterated between until convergence. These simulations will provide a predict-first computation of the ablation rate and dynamics in an upcoming DIII-D experiment that seeks to measure the ablation rate of small neon pellets. The eventual goal is validation of the impurity and ablation models used in the MHD codes for disruption-mitigation modeling.