Titre :

Overview of Gaussian process based multi-fidelity techniques with variable relationship between fidelities, application to aerospace systems

Auteur(s) :

Brevault, Loïc [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]

Titre de la revue :

Aerospace Science and Technology

Pagination :

106339

Éditeur :

Elsevier

Date de publication :

2020-12

ISSN :

1270-9638

Mot(s)-clé(s) en anglais :

Gaussian process
Multi-fidelity
Aerospace system analysis

Discipline(s) HAL :

Statistiques [stat]/Machine Learning [stat.ML]
Sciences de l'ingénieur [physics]
Informatique [cs]
Physique [physics]

Résumé en anglais : [en]

The design process of complex systems such as new configurations of aircraft or launch vehicles is usually decomposed in different phases which are characterized by the depth of the analyses in terms of number of design ...
Lire la suite >The design process of complex systems such as new configurations of aircraft or launch vehicles is usually decomposed in different phases which are characterized by the depth of the analyses in terms of number of design variables and fidelity of the physical models. At each phase, the designers have to deal with accurate but computationally intensive models as well as cheap but inaccurate models. Multi-fidelity modeling is a way to merge different fidelity models to provide engineers with accurate results with a limited computational cost. Within the context of multi-fidelity modeling, approaches based on Gaussian Processes emerge as popular techniques to fuse information between the different fidelity models. The relationship between the fidelity models is a key aspect in multi-fidelity modeling. This paper provides an overview of Gaussian process-based multi-fidelity modeling techniques for variable relationship between the fidelity models (e.g., linearity, non-linearity, variable correlation). Each technique is described within a unified framework and the links between the different techniques are highlighted. All approaches are numerically compared on a series of analytical test cases and four aerospace related engineering problems in order to assess their benefits and disadvantages with respect to the problem characteristics.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL