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Optimizing RF Gun Cavity Geometry within an Automated Injector Design System *

This study presents an innovative approach to optimizing the geometry of RF gun cavities within an automated injector design system, authored by Alicia Hofler and Pavel Evtushenko from the Thomas Jefferson National Accelerator Facility. We address the challenges of geometry tuning and field flatness, demonstrating the iterative nature of our tuning algorithm. Future plans involve refining the algorithm to achieve improved resonance and flatness, ultimately facilitating the extension to a 3.5-cell cavity system. This research contributes significantly to the fields of accelerator physics and injector design.

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Optimizing RF Gun Cavity Geometry within an Automated Injector Design System *

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  1. Optimizing RF Gun Cavity Geometry within an Automated Injector Design System* Alicia Hofler and Pavel Evtushenko Thomas Jefferson National Accelerator Facility Newport News, VA 23606, U.S.A. Particle Accelerator Conference March 28 - April 1, 2011, New York *Authored by JSA, LLC under U.S. DOE Contract DE-AC05-06OR23177. The U.S. Govt. retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce this for U.S. Govt. purposes.

  2. Outline • Problem overview • Geometry description • Geometry tuning • Tuning and field flatness • Future plans and conclusions

  3. Progression of Injector Design Approaches S/RF Gun Injector Design Automation Injector Design Automation1,3 Semi-Automated Injector Design General Purpose Evolutionary Algorithm Based System2 General Purpose Evolutionary Algorithm Based System2 Parameter scans Injector Beam Dynamics Code Injector Beam Dynamics Code Injector Beam Dynamics Code 1 I. V. Bazarov and C. K. Sinclair, PRST-AB 8, 2005. 2 S. Bleuler, et al., Evolutionary Multi-Criterion Optimization (EMO 2003), Faro, Portugal, 2003. 3 F. Hannon, et al., PAC 2011, WEP288. Cavity Field Variation

  4. Cavity Field Variation Theoretical (Cavity Independent)1 More Realistic (Vary Cavity Geometry) 2 Vary Geometry Call Field Solver Optimization System Optimization System Vary Geometry Call Field Solver Optimization System Vary Assumed Field Profile Catalogue of Field Profiles 1 A. Hofler, et al., ICAP 2009. 2 I. V. Bazarov, et al., ERL 2009.

  5. Geometry Description Entrance Wall Exit Wall • Assumptions • Cylindrically symmetric • Two components • Beam tubes • Cells Cell Wall Angles -90o < θ < 90o Cell Base Width Cell Radius Cell Offsets Length Neck Offsets Neck Width Radii of Irises Radius

  6. Geometry Tuning • Goals: • π mode at desired resonance frequency • reasonable to build • quick and reliable • Algorithm • Tunes whole structure • Assumes linear relationship between tuning parameter and tuning goal • Iterative • Alternates between tuning goals • Findings • Tuning for frequency alone insufficient → poor flatness • Alternating between goals does not always converge • Consider multi-variable methods • Need “independent” cavity tuning parameters * S. An and H. Wang, JLAB-TN-03-043 or SNS-NOTE-AP119, 2003.

  7. Dependence of π Mode Frequency on Cell Radii for 1.5 Cell RF Gun Radius 1 Radius 2 • VariedCell radii • 8.55 cm ≤ r ≤ 9.5 cm

  8. Dependence of π Mode Field Flatness on Cell Radii for 1.5 Cell RF Gun • Small set of radii produce 1300 MHz cavity with field flatness < 100 %

  9. Future Plans and Conclusions • Framework for optimizing gun cavity geometry in injector design exists • Success depends on quick and reliable cavity tuning algorithm • Improved tuning algorithm • Resonance and field flatness tuning • Continue tuning studies • Find cavity parameters to affect field flatness with minimal impact on resonance frequency • Beam tube radius • Beam tube length • Extend to 3.5 cell cavity

  10. Thank you.

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