Advances in automatic thermal model to test correlation in space industry

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46th International Conference on Environmental Systems

In space industry thermal models are an important tool to predict, analyze and understand the thermal behaviour of components, subsystems and whole spacecrafts. Most parameters of these models have a limited accuracy and consequently the models results are uncertain. In order to reduce this uncertainty to a required level the model parameters are adjusted (correlated) by fitting the model to test results obtained during thermo vacuum tests. This is often a difficult long lasting manual process. In order to perform these correlations automatically many different methods have been developed and analyzed. Two of these methods are analyzed regarding their requirements, efficiency and limitations. A genetic algorithm is compared to a method based on non-linear equations solving algorithms of the Broyden class.

Tesat Spacecom
TECNALIA, Industry and Transport Division
Mechanical Engineering Department, University of the Basque Country UPV/EHU
ICES207: Thermal and Environmental Control Engineering Analysis and Software
Vienna, Austria
Jan Klement, Tesat-Spacecom GmbH & Co, Germany
Eva Anglada, TECNALIA, Spain
Iñaki Garmendia, University of the Basque Country, Spain
The 46th International Conference on Environmental Systems was held in Vienna, Austria, USA on 10 July 2016 through 14 July 2016.
thermal model, correlation, thermo vaccum test, Fitting, genetic algorithms, Broyden class algorithms