7–12 May 2023
Venice, Italy
Europe/Zurich timezone

Accurate, quasi-3D modeling of single-beam and multiple-beam klystrons and iots by the Tesla-family of large-signal codes

WEPM024
10 May 2023, 16:30
2h
Sala Mosaici 2

Sala Mosaici 2

Poster Presentation MC7.T08: RF Power Sources Wednesday Poster Session

Speaker

Igor Chernyavskiy (Naval Research Laboratory)

Description

Klystrons and IOTs are widely used in accelerators as high-power RF sources. Development and optimization of klystron and IOT designs is aided by the use of different simulation tools, including highly efficient large-signal codes. We present an overview of the advances in the code development and modeling using Naval Research Laboratory (NRL) set of TESLA-family of large-signal codes, suitable for the modeling of single-beam and multiple beam klystrons (MBKs) and IOTs. Original 2.5D large-signal algorithm of the code TESLA was developed for the modeling of klystrons based on (relatively) high Q resonators and is applicable to the multiple-beam devices in an approximation of identical beams/beam-tunnels. Parallel extension of TESLA algorithm (code TESLA-MB enabled an accurate, quasi-3D modeling of multiple-beam devices with non-identical beams/beam-tunnels. Added into TESLA algorithm procedure for proper treatment of ‘slow’ and ‘reflected’ particles enabled accurate modeling of high-efficiency klystrons and contributed into the development of klystron with 80% efficiency. Recently developed more general TESLA-Z algorithm*** is based on the impedance matrix approach and enabled accurate, geometry-driven large-signal modeling of devices with such challenging elements as multiple-gap cavities and filter-loading. Examples of applications of TESLA-family of codes to the modeling of advanced single-beam and multiple-beam klystrons and IOTs will be presented.

Funding Agency

Work was supported by the U.S. Office of Naval Research.

Footnotes

A.N. Vlasov, et al., IEEE TPS, vol. 30, no. 3, pp.1277-1291, June 2002.
I.A. Chernyavskiy, et al., IEEE TED, vol. 54, no.6, pp.1555-1561, June 2007.
I.A. Chernyavskiy, et al., IEEE TPS, vol. 36, no. 3, pp.670-681, June 2008.
M. Read, T. Haberman, A. Jensen, R.L. Ives, 22nd IVEC, 2021.
***I.A. Chernyavskiy et al., IEEE TED, vol. 64, no. 2, pp. 536-542, Feb. 2017.

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Author

Igor Chernyavskiy (Naval Research Laboratory)

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