On the Ramifications of Geometrical Uncertainties Upon Performance Parameters of TWT

• Published in: IEEE transactions on electron devices 2023-08, Vol.70 (8), p.1-8
• Main Authors: Liu, Kegang, Ding, Haibing, Xue, Qianzhong, Guo, Naining, Song, Wenke, Xie, Bingchuan, Zhao, Ding
• Format: Article
• Language: English
• Subjects: Artificial neural network (ANN); Artificial neural networks; Bandwidth; Corrugated waveguides; Gain; geometrical uncertainties; Geometry; insert phase; Interaction parameters; Manufacturing; manufacturing yield; Monte Carlo method; Performance analysis; Performance indices; Traveling wave tubes; Traveling waves; traveling-wave tube (TWT); Uncertainty; uncertainty analysis
• ISSN: 0018-9383; 1557-9646
• DOI: 10.1109/TED.2023.3288843

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).