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International Journal of Aerospace Engineering
Volume 2017 (2017), Article ID 7683457, 12 pages
Research Article

Performance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecrafts

1Industry and Transport Division, TECNALIA, Mikeletegi Pasealekua 2, 20009 San Sebastián (Donostia), Spain
2Mechanical Engineering Department, Engineering School of Gipuzkoa, University of the Basque Country (UPV/EHU), Plaza de Europa 1, 20018 San Sebastián (Donostia), Spain

Correspondence should be addressed to Eva Anglada

Received 30 January 2017; Revised 11 April 2017; Accepted 26 April 2017; Published 24 May 2017

Academic Editor: Paolo Tortora

Copyright © 2017 Eva Anglada et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The correlation of the thermal mathematical models (TMMs) of spacecrafts with the results of the thermal test is a demanding task in terms of time and effort. Theoretically, it can be automatized by means of optimization techniques, although this is a challenging task. Previous studies have shown the ability of genetic algorithms to perform this task in several cases, although some limitations have been detected. In addition, gradient-based methods, although also presenting some limitations, have provided good solutions in other technical fields. For this reason, the performance of genetic algorithms and gradient-based methods in the correlation of TMMs is discussed in this paper to compare the pros and cons of them. The case of study used in the comparison is a real space instrument flown aboard the International Space Station.