Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp012n49t492r
Title: Energetic particle optimization of quasi-axisymmetric stellarator equilibria
Contributors: LeViness, Alexandra
Schmitt, John
Lazerson, Samuel
Bader, Aaron
Faber, Benjamin
Hammond, Kenneth
Gates, David
U. S. Department of Energy contract number DE-AC02-09CH11466
Issue Date: 2022
Publisher: Princeton Plasma Physics Laboratory, Princeton University
Related Publication: Nuclear Fusion, in press
Abstract: An important goal of stellarator optimization is to achieve good confinement of energetic particles such as, in the case of a reactor, alphas created by Deuterium-Tritium (D-T) fusion. In this work, a fixed-boundary stellarator equilibrium was re-optimized for energetic particle confinement via a two-step process: first, by minimizing deviations from quasi-axisymmetry (QA) on a single flux surface near the mid-radius, and secondly by maintaining this improved quasi-axisymmetry while minimizing the analytical quantity ΓC , which represents the angle between magnetic flux surfaces and contours of J||, the second adiabatic invariant. This was performed multiple times, resulting in a group of equilibria with significantly reduced energetic particle losses, as evaluated by Monte Carlo simulations of alpha particles in scaled-up versions of the equilibria. This is the first time that energetic particle losses in a QA stellarator have successfully been reduced by optimizing ΓC . The relationship between energetic particle losses and metrics such as QA error (Eqa) and ΓC in this set of equilibria were examined via statistical methods and a nearly linear relationship between volume-averaged ΓC and prompt particle losses was found.
URI: http://arks.princeton.edu/ark:/88435/dsp012n49t492r
Referenced By: https://doi.org/10.1088/1741-4326/aca4e3
Appears in Collections:Stellarators

Files in This Item:
File Description SizeFormat 
data.zip62.69 kBUnknownView/Download
README.txt9.16 kBTextView/Download


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.