Thermal Stability Analysis of Superconducting RF Cavities

  • T. Junquera
  • J. Lesrel
  • M. Fouaidy
  • S. Bousson
Part of the Advances in Cryogenic Engineering book series (ACRE, volume 43)

Abstract

Future linear accelerators using superconducting RF cavities (TESLA proposal), requires accelerating gradients Eacc=25 MV/m to be achieved reliably at large scale. This high gradient level is mainly limited by electron emission and thermal instabilities (quench). Impressive improvements have been recently accomplished by pushing further the onset threshold of electron emision using careful surface cleaning techniques. On the other side micron size resistive defects embedded in the niobium walls of the cavity continue to induce thermal breakdowns for Eacc in the range 15 to 25 MV/m. In this paper the thermal stability of SRF cavities is analysed using analytical and numerical simulation models. The effects of the most relevant parameters (i.e. defect size, RF frequency, thermal conductivity, cooling conditions, etc.) having an incidence on the cavity quench are studied. The steady-state and the transient solutions are presented in two cases : the defect free surface, and the micron size defect on the cavity surface. Experimental observations of the thermal events occuring during the quench have been obtained with the help of two diagnostic systems: surface thermometers working in superfluid helium and RF measurements. All the proposed experimental and modelling methods could contribute to get a more complete insight on the thermal effects taking place in the cavity wall.

Keywords

Defect Size Thermal Instability Cavity Wall Finite Element Code Cavity Field 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    G. Muller. Proceed. 3rd. Workshop on RF Superconductivity. Report ANL-PHY 88–1, Argonne USAGoogle Scholar
  2. 2.
    J.Tuckmantel. Report CERN/EF/RF 84–6, CERN, Geneva 1984Google Scholar
  3. 3.
    H. Safa. Proceed. 7th Workshop on RF Superconductivity. October 1995, Gif-sur-Yvette, FranceGoogle Scholar
  4. 4.
    X. Cao and D. Proch. IEEE Particle Conference. May 1991, San Francisco USAGoogle Scholar
  5. 5.
    Handbook on Materials for Superconducting Machinery. Nov. 1974, Batelles Columbus Lab. USAGoogle Scholar
  6. 6.
    M. Fouaidy et al. Proceed. 5th. Workshop on RF Superconductivity. Report DESY M-92–01, GermanyGoogle Scholar
  7. 7.
    Boucheffa et al. Proceed. 7th Workshop on RF Superconductivity. Oct. 1995, Gif-sur-Yvette, FranceGoogle Scholar
  8. 8.
    W. Weingarten CERN report 92–03 vol II. June 1992, CERN, GenevaGoogle Scholar
  9. 9.
    “Conduction of Heat in Solids” HS. Carslaw and J.C. Jaeger, 2nd edition. Oxford Univ. Press 1959Google Scholar
  10. 10.
    Castem 2000. Report DEMT 88/176 . CEA Saclay, FranceGoogle Scholar
  11. 11.
    J. Graber et al. Report CLNS 91–1061 Cornell Univ. Ithaca NY, USAGoogle Scholar
  12. 12.
    M. Pekeler. Ph.D. Thesis. Report DESY M-96–16, Hamburg, GermanyGoogle Scholar
  13. 13.
    Modulef (1988). INRIA-Simulog, Rocquencourt Le Chesnay , FranceGoogle Scholar
  14. 14.
    Q.S. Shu et al. Applied Superconductivity Conference (1996). Pittsburgh, PA, USAGoogle Scholar
  15. 15.
    TESLA Collaboration Report 97–05. DESY, Hamburg, Germany.Google Scholar
  16. 16.
    Tom Hays: « http://w4.lns.cornell.edu/~trh/fondue/ »Google Scholar
  17. 17.
    M. Fouaidy et al. Proceed. 7th Worksop on RF Superconductivity. Oct. 1995, Gif-sur-Yvette, FranceGoogle Scholar
  18. 18.
    D. Reschke and R. Roth. Proceed. 6th. Workshop on RF Superconductivity. CEBAF 1993. VA, USAGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • T. Junquera
    • 1
  • J. Lesrel
    • 1
  • M. Fouaidy
    • 1
  • S. Bousson
    • 1
  1. 1.Institut de Physique Nucleaire (CNRS-IN2P3)OrsayFrance

Personalised recommendations