Improved Methodology to Estimate the Power Transfer Efficiency in an Inductively Coupled Radio Frequency Ion Source

Palak Jain, Mauro Recchia, Pierluigi Veltri, Marco Cavenago, Alberto Maistrello, Elena Gaio

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Abstract

The International Thermonuclear Experimental Reactor neutral beam injector includes an ion source which can produce D-ion beams for 1 h, accelerated at the energy of 1 MeV. An ion source consists of a driver where the plasma is produced by the application of the radio frequency (RF) power to an inductive coil. This paper presents an improved methodology which provides an estimation of the power transfer efficiency to the plasma of the driver. The developed methodology is based on different mechanisms which are responsible for the plasma heating (ohmic and stochastic) and an electrical model describing the power transfer to the plasma. As a first approximation in a previous work, a transformer model was assumed as an electrical model. In this paper, a main improvement is introduced based on the development of a multi-filament model which takes into account the mutual coupling between the RF coil, the plasma, and the passive metallic structure. The methodology is applied to the negative ion optimization 1 (NIO1), a flexible negative ion source, currently in operation at Consorzio RFX, Italy. The results from the two models, transformer and multi-filament, are presented and compared in terms of plasma equivalent resistance and power transfer efficiency. It is found that results obtained from both the transformer and the multi-filament model follow the same trend in comparison with the applied frequency and the other plasma parameters like electron density, temperature, and gas pressure. However, lower values of the plasma equivalent resistance and power transfer efficiency are observed with the multi-filament model. The multi-filament model reproduces a more realistic experimental scenario where the power losses due to the generation of the eddy currents in the metallic structure are considered.
Original languageEnglish
Pages (from-to)29665 - 29676
Number of pages12
JournalIEEE Access
Volume6
DOIs
Publication statusPublished - 24 Apr 2018
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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