Performance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecrafts
Joint Authors
Anglada, Eva
Martinez-Jimenez, Laura
Garmendia, Iñaki
Source
International Journal of Aerospace Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-24
Country of Publication
Egypt
No. of Pages
12
Abstract EN
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.
American Psychological Association (APA)
Anglada, Eva& Martinez-Jimenez, Laura& Garmendia, Iñaki. 2017. Performance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecrafts. International Journal of Aerospace Engineering،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1158158
Modern Language Association (MLA)
Anglada, Eva…[et al.]. Performance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecrafts. International Journal of Aerospace Engineering No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1158158
American Medical Association (AMA)
Anglada, Eva& Martinez-Jimenez, Laura& Garmendia, Iñaki. Performance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecrafts. International Journal of Aerospace Engineering. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1158158
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1158158