Thermal performance verification of the SIRTF cryogenic telescope assembly

Details Thermal performance verification of the SIRTF cryogenic telescope assembly Thermal performance verification of the SIRTF cryogenic telescope assembly

Mar 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003spie.4850...72f&link_type=abstract

IR Space Telescopes and Instruments. Edited by John C. Mather . Proceedings of the SPIE, Volume 4850, pp. 72-82 (2003).

Computer Science

Performance

1

Scientific paper

The SIRTF Cryogenic Telescope Assembly employs a multi-stage thermal/cryogenic system in which the telescope is cooled bo 5.5K by passive techniques combined with vapor cooling by the effluent from a superfluid helium cryostat. The cryostat and telescope are surrounded by an outer shell, which is passively cooled to an expected temperature of about 35K. Verifying the performance of this system by test cannot be practically accomplished by a single end-to-end test. In the SIRTF-CTA Performance Test, we verified the relationship between helium flow rate and telescope temperature with the outer shell held at its predicted flight temperature. For systems like the SIRTF-CTA with thermal time constraints of several days, schedule is a critical parameter when planning the test procedure. The original plan of two steady-state tests at two different flight-like thermal boundary conditions was supplemented when we discovered that the test-induced (background) heat load to the cryostat and telescope was an order of magnitude larger than the predicted flight levels. With these unforeseen heat loads, we amended the test plan to include multiple changes to the test boundary conditions to quantify the background heat sources. Because of schedule constraints, we did not h ave the luxury of establishing steady-state for the various conditions of interest, and we relied on analysis of the system transient response for verification. Here we present our investigation of test-induced heat loads, our approach to data analysis, a comparison of measured system performance to analytical predictions, and some lessons learned.

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