On the Ramifications of Geometrical Uncertainties Upon Performance Parameters of TWT

It's presented here a general pattern for quantitative evaluation of impacts imposed by uncertainties brought directly from geometrical parameters on performance parameters for traveling-wave tube (TWT) design, in a holistic perspective in terms of distribution traits. For the sake of generality and built-up of pathways, artificial neural network (ANN), rather than closed-form solution, is employed for access to the mapping between geometrical parameters with interaction parameters, involving interaction impedance, detune parameter and attenuation constant. Furthermore, with the intermediate interaction parameters derived, the geometrical variations are eventually connected with TWT performance indexes like gain, bandwidth, insertion phase and even manufacturing yield. With such an ease on the association between the two somewhat distant analysis layers in general, a Monte-Carlo analysis is carried out to reveal the ramifications brought from multi-dimensional geometrical uncertainties on performance indexes. An embodiment of the analysis approach is made with double corrugated waveguide (DWC).

Automated summary

A general pattern for quantitative evaluation of the impacts of geometrical uncertainties on TWT performance parameters is presented using a holistic perspective. Artificial neural network (ANN) is employed to establish the mapping between geometrical parameters and interaction parameters. Monte-Carlo analysis is used to reveal the ramifications of multi-dimensional geometrical uncertainties on TWT performance indexes. An embodiment of the approach is demonstrated with DWC.