Uncertainty in the isosceles multipactor threshold of triangularly grooved surfaces based on polynomial chaos

The success of future synchrotron radiation sources will be closely linked with the development of high-brightness continuous-wave capable electron injectors. Superconducting radiofrequency (SRF) photo injectors, as operated at the Helmholtz-Zentrum Dresden-Rossendorf among others, are a promising a...

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Veröffentlicht in:Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment Accelerators, spectrometers, detectors and associated equipment, 2021-03, Vol.993, p.165001, Article 165001
Hauptverfasser: Mostajeran, Maryam, Tulu, Eden Tafa, van Rienen, Ursula
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Sprache:eng
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Zusammenfassung:The success of future synchrotron radiation sources will be closely linked with the development of high-brightness continuous-wave capable electron injectors. Superconducting radiofrequency (SRF) photo injectors, as operated at the Helmholtz-Zentrum Dresden-Rossendorf among others, are a promising approach for this purpose. Yet, the reliability of electron sources can be significantly limited by electron multipacting (MP), a very common phenomenon in radio frequency (RF) vacuum devices. In a previous study it was shown that the choice of grooved surfaces for the cathode stem promises to be a good measure to suppress MP. The accuracy of the MP threshold is mainly determined by the uncertainty of secondary emission properties of the material. In the past, to determine the MP thresholds in various RF devices, numerous experiments and numerical simulation studies have been conducted worldwide. Nevertheless, there is no particular study to be found on the observed uncertainty in MP thresholds. In this paper, the influence of uncertainty in secondary electron yield (SEY) parameters on the MP threshold of surfaces with isosceles triangular grooves is investigated using the generalized polynomial chaos (gPC) method that allows an efficient representation of random field solutions to partial differential equations with random data.
ISSN:0168-9002
1872-9576
DOI:10.1016/j.nima.2020.165001