Impact of a minority relativistic electron tail interacting with a thermal plasma containing high-atomic-number impurities

Abstract

A minority relativistic electron component can arise in both laboratory and naturally-occurring plasmas. In the presence of high-atomic-number ion species, the ion charge state distribution at low bulk electron temperature can be dominated by relativistic electrons, even though their density is orders of magnitude lower. This is due to the relativistic enhancement of the collisional excitation and ionization cross sections. The resulting charge state effect can dramatically impact the radiative power loss rate and the related Bethe stopping power of relativistic electrons in a dilute plasma. (Approved for release under LA-UR-19-28749)

DREAM: a fluid-kinetic framework for tokamak disruption runaway electron simulations

“…ion,i are taken as in Ref. [48], which extended the validity of the Burgess-Chidichimo model [49] to relativistic energies, with the momentum integration limits taken as in section (2.2). Unlike the cited studies where model parameters were chosen from atomic data, Dream uses parameters which have been fitted to the OpenADAS ionization coefficients in the lowdensity (coronal) limit when the distribution is taken to be a Maxwellian for a range of temperatures, assuming that a single shell dominates the ionization.…”

Efficient data acquisition and training of collisional-radiative model artificial neural network surrogates through adaptive parameter space sampling

“…Modeling and simulations are a major tool being used to perform these studies, with many plasma simulation codes coupling multiple modules to better describe the wide array of physics phenomena taking place within the plasmas being considered [3][4][5][6][7]. One key component in the plasma simulation cycle is to accurately describe the collisional-radiative (CR) balance of the plasma, in order to determine impurity ion populations, and the radiation being emitted by the excited ion populations within the plasma at a given time and location [8][9][10][11].…”

“…Relatively compact approximate CR models, with state vectors O(10 1 -10 2 ) such as that used in this present work [9,18], can take up to dozens of seconds to solve. While state-of-the-art, fine structure O(10 6 -10 9 ) CR models can take minutes or hours to obtain a solution [11,19].…”

Efficient training of artificial neural network surrogates for a collisional-radiative model through adaptive parameter space sampling

“…Modeling and simulations are a major tool for such studies, with many plasma simulation codes that integrate multiple physics modules to better describe the wide array of physics phenomena taking place within the plasmas [3,4,5,6,7]. One key component in fusion plasma simulations is to accurately describe the collisional-radiative balance of the plasma, in order to determine impurity ion populations, and the radiation being emitted by the excited ion populations within the plasma at a given time and location [8,9,10,11].…”

“…Relatively compact approximate CR models, with state vectors O(10 1 − 10 2 ) such as that used in this present work [18,9], can take up to dozens of seconds to solve. The state-of-the-art, fine structure O(10 6 − 10 9 ) CR models can take minutes or hours to obtain a solution [11,19].…”