Multi-Objective Multidisciplinary Design ...
Document type :
Article dans une revue scientifique
DOI :
Title :
Multi-Objective Multidisciplinary Design Optimization Approach for Partially Reusable Launch Vehicle Design
Author(s) :
Brevault, Loic [Auteur]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Balesdent, Mathieu [Auteur]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Hebbal, Ali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Balesdent, Mathieu [Auteur]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Hebbal, Ali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Journal title :
Journal of Spacecraft and Rockets
Pages :
373-390
Publisher :
American Institute of Aeronautics and Astronautics
Publication date :
2020-03
ISSN :
0022-4650
Keyword(s) :
VEHICULE AEROSPATIAL
English keyword(s) :
MDO - Multi-Disciplinary Optimization
HAL domain(s) :
Statistiques [stat]/Machine Learning [stat.ML]
English abstract : [en]
Reusability of the first stage of launch vehicles may offer new perspectives to lower the cost of payload injection into orbit if sufficient reliability and efficient refurbishment can be achieved. One possible option that ...
Show more >Reusability of the first stage of launch vehicles may offer new perspectives to lower the cost of payload injection into orbit if sufficient reliability and efficient refurbishment can be achieved. One possible option that may be explored is to design the vehicle first stage for both reusable and expendable uses, in order to increase the flexibility and adaptability to different target missions. This paper proposes a multilevel multidisciplinary design optimization (MDO) approach to design aerospace vehicles addressing multimission problems. The proposed approach is focused on the design of a family of launchers for different missions sharing commonalities using multi-objective MDO to account for the computational cost associated with the discipline simulations. The multimission problem addressed considers two missions: 1) a reusable configuration for a sun synchronous orbit with a medium payload range and recovery of the first stage using a gliding-back strategy; 2) an expendable configuration for a medium payload injected into a geostationary transfer orbit. A dedicated MDO formulation introducing couplings between the missions is proposed in order to efficiently solve such a coupled problem while limiting the number of calls to the exact multidisciplinary analysis thanks to the use of Gaussian processes and multi-objective efficient global optimization.Show less >
Show more >Reusability of the first stage of launch vehicles may offer new perspectives to lower the cost of payload injection into orbit if sufficient reliability and efficient refurbishment can be achieved. One possible option that may be explored is to design the vehicle first stage for both reusable and expendable uses, in order to increase the flexibility and adaptability to different target missions. This paper proposes a multilevel multidisciplinary design optimization (MDO) approach to design aerospace vehicles addressing multimission problems. The proposed approach is focused on the design of a family of launchers for different missions sharing commonalities using multi-objective MDO to account for the computational cost associated with the discipline simulations. The multimission problem addressed considers two missions: 1) a reusable configuration for a sun synchronous orbit with a medium payload range and recovery of the first stage using a gliding-back strategy; 2) an expendable configuration for a medium payload injected into a geostationary transfer orbit. A dedicated MDO formulation introducing couplings between the missions is proposed in order to efficiently solve such a coupled problem while limiting the number of calls to the exact multidisciplinary analysis thanks to the use of Gaussian processes and multi-objective efficient global optimization.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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