Design Prediction of TWT Collector using Data Science
IR@CEERI: CSIR-Central Electronics Engineering Research Institute, Pilani
View Archive Info| Field | Value | |
| Title |
Design Prediction of TWT Collector using Data Science
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| Creator |
Pareek , N
Latha, AM Ghosh , SK |
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| Subject |
Travelling Wave Tubes
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| Description |
A Multistage depressed collector (MDC) is a critical
component of traveling wave tubes (TWT) and contribute major share of the TWT overall efficiency, and hence, needs special consideration in designing such MDC for very high efficiency TWT. In this paper, a data-driven approach to model high efficiency MDC has been presented. A series,of spent-beam data has been generated from the beam-wave interaction software, SUNRAY and subsequently, the data has been analyzed using k-means clustering .The depressed electrode potentials obtained via data clustering, gave an efficiency of 82.8 %. This new approach is much faster then the conventional approach reported eslewhere.
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| Date |
2019
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| Type |
Conference or Workshop Item
PeerReviewed |
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| Format |
application/pdf
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| Identifier |
http://ceeri.csircentral.net/500/1/252019%284%29.pdf
Pareek , N and Latha, AM and Ghosh , SK (2019) Design Prediction of TWT Collector using Data Science. In: National Symposium on Vaccum Electronic Devices and Applications(VEDA-2019), November 21-23, 2019, NIT, Patna, India. |
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| Relation |
http://ceeri.csircentral.net/500/
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