Optimizing Space Telescopes’ Thermal Performance through Uncertainty Analysis: Identification of Critical Parameters and Shaping Test Strategy Development

Author:

Garcia-Luis Uxia1ORCID,Gomez-San-Juan Alejandro M.1,Navarro-Medina Fermin1ORCID,Ulloa-Sande Carlos1,Yñigo-Rivera Alfonso2,Peláez-Santos Alba Eva3

Affiliation:

1. Escola de Enxeñaría Aeronautica e do Espazo, Aerospace Technology Research Group, atlanTTic, Universidade de Vigo, Pabellón Manuel Martínez-Risco, As Lagoas, S/N, 32004 Ourense, Ourense, Spain

2. Instituto de Astrofísica de Canarias (IAC), c/ Via Láctea, S/N, 38205 La Laguna, Tenerife, Spain

3. ESA-ESTEC, co ATG Europe BV, Keplerlaan 1, 2201AZ Noordwijk, The Netherlands

Abstract

The integration of uncertainty analysis methodologies allows for improving design efficiency, particularly in the context of instruments that demand precise pointing accuracy, such as space telescopes. Focusing on the VINIS Earth observation telescope developed by the Instituto de Astrofísica de Canarias (IAC), this paper reports an uncertainty analysis on a thermal model aimed at improving cost savings in the future testing phases. The primary objective was to identify critical parameters impacting thermal performance and reduce overdesign. Employing the Statistical Error Analysis (SEA) method across several operational scenarios, the research identifies key factors, including the Earth’s infrared temperature and albedo, and the spacecraft’s attitude and environmental conditions, as the variables with major influences on the system’s thermal performance. Ultimately, the findings suggest that uncertainty-based analysis is a potent tool for guiding thermal control system design in space platforms, promoting efficiency and reliability. This methodology not only provides a framework for optimizing thermal design and testing in space missions but also ensures that instruments like the VINIS telescope maintain optimal operating temperatures in diverse space environments, thereby increasing mission robustness and enabling precise resource allocation.

Publisher

MDPI AG

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