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Zhao, L.

Paper Title Page
TUPAS078 Status of FAR-TECH's ECR Ion Source Optimization Modeling 1829
 
  • J. S. Kim, I. N. Bogatu, B. Cluggish, S. Galkin, L. Zhao
    Far-Tech, Inc., San Diego, California
  • R. C. Pardo
    ANL, Argonne, Illinois
  • V. Tangri
    UW-Madison/PD, Madison, Wisconsin
 
  Funding: Work supported by the US Department of Energy, under a SBIR grant No. DE-FG02-04ER83954.

The electron cyclotron-resonance ion source (ECRIS) is one of the most efficient ways to provide high-quality, high-charge-state ion beam for research and development of particle accelerators and atomic physics experiments. For ECR ion source performance optimization, FAR-TECH Inc. is developing an integrated suite of computer codes: the Generalized ECRIS plasma Modeling code (GEM), the MCBC (Monte Carlo Beam Capture) module, to study beam capture and charge-breeding processes in ECRIS, and the extraction section code. Our recent progress includes the following: algorithm update of Coulomb collision in MCBC for more accurate calculations of the beam capture efficiency, which depends on beam energy and the background plasma, 2D extension of GEM by adding the radial dimension, and the ion extraction section modeling using an adaptive technique.

 
TUPAS079 2D Extension of GEM (The Generalized ECR Ion Source Modeling Code) 1832
 
  • L. Zhao, B. Cluggish, J. S. Kim
    Far-Tech, Inc., San Diego, California
 
  Funding: Work supported by the US Department of Energy, under a SBIR grant No. DE-FG02-04ER83954

To model ECRIS, GEM is being extended to 2D by adding radial dimension. The electron distribution function (EDF) is calculated on each magnetic flux surface using a bounce-averaged Fokker-Planck code with 2D ECR heating (ECRH) modeling. The ion fluid model is also being extended to 2D by adding collisional radial transport terms. All species in ECRIS are balanced by keeping the neutrality in each cell and the plasma potential is calculated by maintaining the ambipolarity globally. The graphical user interface (GUI) and parallel computing ability of GEM make it an easy-to-use tool for ECRIS research. Numerical results and comparisons with experimental data will be presented.