Gas-Puff Z-Pinch Simulations Using Cell-Centered Divergence Cleaning
ORAL
Abstract
Z-pinches are a widely studied method for plasma confinement in fusion research. To better
understand and optimize plasma behavior, both experiments and numerical simulations are
employed - particularly for gas-puff Z-pinches, which offer a flexible platform for studying plasma
dynamics and instability development. In this work, we present simulation results of COBRA Z-
pinch experiments, focusing on the behavior of triple gas-puff injectors under purely toroidal
magnetic fields. These simulations explore the evolution of the implosion and the growth of
magnetohydrodynamic instabilities. We use the FLASH code [Fryxell et al. Astrophys. J. Suppl.
Ser. 131, 273, 2000; Tzeferacos et al. High Energy Density Phys. 17, 24, 2015] to model the system
dynamics, incorporating a newly implemented cell-centered divergence cleaning method based on
the Generalized Lagrange Multiplier (GLM) approach [Mignone & Tzeferacos, J. Comput. Phys.
229, 2117, 2010], which ensures solenoidality in the magnetic field evolution.
understand and optimize plasma behavior, both experiments and numerical simulations are
employed - particularly for gas-puff Z-pinches, which offer a flexible platform for studying plasma
dynamics and instability development. In this work, we present simulation results of COBRA Z-
pinch experiments, focusing on the behavior of triple gas-puff injectors under purely toroidal
magnetic fields. These simulations explore the evolution of the implosion and the growth of
magnetohydrodynamic instabilities. We use the FLASH code [Fryxell et al. Astrophys. J. Suppl.
Ser. 131, 273, 2000; Tzeferacos et al. High Energy Density Phys. 17, 24, 2015] to model the system
dynamics, incorporating a newly implemented cell-centered divergence cleaning method based on
the Generalized Lagrange Multiplier (GLM) approach [Mignone & Tzeferacos, J. Comput. Phys.
229, 2117, 2010], which ensures solenoidality in the magnetic field evolution.
*This material is based on work supported by the U.S. Department of Energy (DOE) NationalNuclear Security Administration (NNSA) under awards DE-NA0004144 and DE-NA0004147,and under subcontracts no. 630138 and C4574 with Los Alamos National Laboratory. Weacknowledge support from the U.S. DOE Advanced Research Projects Agency-Energy (ARPA-E)under Award Number DE-AR0001272, and the U.S. DOE Office of Science (SC) under AwardNumber DE-SC0023246. The software used in this work was developed in part by the U.S. DOENNSA- and U.S. DOE Office of Science-supported Flash Center for Computational Science at theUniversity of Chicago and the University of Rochester.
–
Presenters
-
Chadi Meskini
- University of Rochester