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Cryocoolers 8 pp 609-621 | Cite as

Ground Testing of a 10 K Sorption Cryocooler Flight Experiment (BETSCE)

  • S. Bard
  • J. Wu
  • P. Karlmann
  • P. Cowgill
  • C. Mirate
  • J. Rodriguez

Abstract

The Brilliant Eyes Ten-Kelvin Sorption Cryocooler Experiment (BETSCE) is a Space Shuttle side-wall-mounted flight experiment designed to demonstrate 10 K sorption cryocooler technology in a space environment. The BETSCE objectives are to: (1) provide a thorough end-to-end characterization and space performance validation of a complete, multistage, automated, closed-cycle hydride sorption cryocooler in the 10 to 30 K temperature range, (2) acquire the quantitative microgravity database required to provide confident engineering design, scaling and optimization, (3) advance the enabling technologies and resolve integration issues, and (4) provide hardware qualification and safety verification heritage.

BETSCE ground tests were the first-ever demonstration of a complete closed-cycle 10 K sorption cryocooler. Test results exceeded functional requirements, as the BETSCE cooler was able to cooldown from 70 K to < 11 K in 95 seconds, sustain a simulated detector heat load of 100 mW for > 20 minutes, achieve a minimum temperature of 9.5 K with load, and demonstrate excellent repeatability with continued cycling. The sorbent beds achieved a compression ratio of 8.3 × 105, and were able to recycle the system in under 5.5 hours. This paper summarizes functional and environmental ground test results, planned characterization tests, important development challenges that were overcome, and valuable lessons-learned. The planned spaceflight experiment will enable early insertion of sorption cryocooler technology into future long-life, low-vibration, spacecraft sensor cooling applications in the 10 to 30 K temperature range.

Keywords

Storage Tank Phase Change Material Liquid Hydrogen Cold Head Pressure Container 
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.

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Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • S. Bard
    • 1
  • J. Wu
    • 1
  • P. Karlmann
    • 1
  • P. Cowgill
    • 1
  • C. Mirate
    • 1
  • J. Rodriguez
    • 1
  1. 1.Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaUSA

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