| Title |
Single Objective Genetic Optimization of an 85% Efficient Klystron |
| Authors |
- 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
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| Abstract |
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.
|
| Paper |
download SAPAF04.PDF [1.258 MB / 5 pages] |
| Slides |
download SAPAF04_TALK.PDF [1.476 MB] |
| Export |
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| Conference |
ICAP2018 |
| Series |
International Computational Accelerator Physics Conference (13th) |
| Location |
Key West, FL, USA |
| Date |
20-24 October 2018 |
| Publisher |
JACoW Publishing, Geneva, Switzerland |
| Editorial Board |
Volker RW Schaa (GSI, Darmstadt, Germany); Kyoko Makino (MSU, East Lansing, MI, USA); Pavel Snopok (IIT, Chicago, IL, USA); Martin Berz (MSU, East Lansing, MI, USA) |
| Online ISBN |
978-3-95450-200-4 |
| Received |
16 October 2018 |
| Accepted |
19 November 2018 |
| Issue Date |
04 May 2019 |
| DOI |
doi:10.18429/JACoW-ICAP2018-SAPAF04 |
| Copyright |
 Published by JACoW Publishing under the terms of the Creative Commons Attribution 3.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |
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