From Event: SPIE Optical Engineering + Applications, 2017
The JWST Optical Telescope Element (OTE) assembly is the largest optically stable infrared-optimized telescope currently being manufactured and assembled, and is scheduled for launch in 2018. The JWST OTE, including the 18 segment primary mirror, secondary mirror, and the Aft Optics Subsystem (AOS) are designed to be passively cooled and operate near 45K. These optical elements are supported by a complex composite backplane structure. As a part of the structural distortion model validation efforts, a series of tests are planned during the cryogenic vacuum test of the fully integrated flight hardware at NASA JSC Chamber A. The successful ends to the thermal-distortion phases are heavily dependent on the accurate temperature knowledge of the OTE structural members. However, the current temperature sensor allocations during the cryo-vac test may not have sufficient fidelity to provide accurate knowledge of the temperature distributions within the composite structure. A method based on an inverse distance relationship among the sensors and thermal model nodes was developed to improve the thermal data provided for the nanometer scale WaveFront Error (WFE) predictions. The Linear Distance Weighted Interpolation (LDWI) method was developed to augment the thermal model predictions based on the sparse sensor information. This paper will encompass the development of the LDWI method using the test data from the earlier ‘pathfinder’ cryo-vac tests, and the results of the notional and as tested WFE predictions from the structural finite element model cases to characterize the accuracies of this LDWI method.
Sang C. Park, Timothy M. Carnahan, Lester M. Cohen, Cherie B. Congedo, Michael J. Eisenhower, Wes Ousley, Andrew Weaver, and Kan Yang, "Augmented method to improve thermal data for the figure drift thermal distortion predictions of the JWST OTIS cryogenic vacuum test," Proc. SPIE 10374, Optical Modeling and Performance Predictions IX, 1037406 (Presented at SPIE Optical Engineering + Applications: August 08, 2017; Published: 6 September 2017); https://doi.org/10.1117/12.2277116.
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