1. Deep learning assisted optimization of Ka-band relativistic backward wave oscillator operating in TM03 mode with low guiding magnetic field.
- Author
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Yang, Wenjin, Li, Yongdong, Wang, Hongguang, Jiang, Ming, Zhai, Yonggui, and Liu, Chunliang
- Subjects
- *
BACKWARD wave oscillators , *MAGNETIC fields , *SLOW wave structures , *DEEP learning , *MICROWAVE devices - Abstract
To accelerate the design of a high-power microwave device, a deep learning assisted multi-objective optimization method is used to optimize a Ka-band relativistic backward-wave oscillator (RBWO) operating with a low magnetic field. Particle-in-cell simulation results show that the optimized RBWO with a tooth-shaped slow wave structure (SWS) can generate microwave pulses with an output power of 1.24 GW and an operating frequency of 26.8 GHz under a diode voltage of 623.3 kV, and the diode current is 6.56 kA at a guiding magnetic field of 0.8 T. Compared with the original RBWO, the output power of the optimized RBWO has been increased by 201.2%, and the beam-to-microwave conversion efficiency has increased from 10.0% to 30.3%. The detailed analysis reveals that in an overmoded RBWO with low guiding magnetic fields, the introduction of a tooth-shaped SWS is beneficial to mode competition, improves output power, and decreases microwave starting time. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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