Author: Petillo, J.J.
Paper Title Page
SAPAF04 Single Objective Genetic Optimization of an 85% Efficient Klystron 25
  • A. Jensen, J.J. Petillo
    Leidos Corp, Billerica, MA, USA
  • R.L. Ives, M.E. Read
    CCR, San Mateo, California, USA
  • J. Neilson
    SLAC, Menlo Park, California, USA
  Overall efficiency is a critical priority for the next generation of particle accelerators as they push to higher and higher energies. In a large machine, even a small increase in efficiency of any subsystem or component can lead to a significant operational cost savings. The Core Oscillation Method (COM) and Bunch-Align-Compress (BAC) method have recently emerged as a means to greatly increase the efficiency of the klystron RF source for particle accelerators. The COM and BAC methods both work by uniquely tuning klystron cavity frequencies such that more particles from the anti-bunch are swept into the bunch before power is extracted from the beam. The single objective genetic algorithm from Sandia National Laboratory’s Dakota optimization library is used to optimize both COM and BAC based klystron designs to achieve 85% efficiency. The COM and BAC methods are discussed. Use of the Dakota optimization algorithm library from Sandia National Laboratory is discussed. Scalability of the optimization approach to High Performance Computing (HPC) is discussed. The optimization approach and optimization results are presented.  
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About • paper received ※ 16 October 2018       paper accepted ※ 19 November 2018       issue date ※ 26 January 2019  
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