Multi-objective Design Optimization Using High-Order Statistics for CFD Applications
| hal.structure.identifier | Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS] | |
| dc.contributor.author | CONGEDO, Pietro Marco | |
| hal.structure.identifier | Department of Mechanical Engineering [Stanford] | |
| dc.contributor.author | GERACI, Gianluca | |
| hal.structure.identifier | Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS] | |
| dc.contributor.author | ABGRALL, Rémi | |
| hal.structure.identifier | Department of Mechanical Engineering [Stanford] | |
| dc.contributor.author | IACCARINO, Gianluca | |
| dc.contributor.editor | David Greiner | |
| dc.contributor.editor | Blas Galván | |
| dc.contributor.editor | Jacques Périaux | |
| dc.contributor.editor | Nicolas Gauger | |
| dc.contributor.editor | Kyriakos Giannakoglou | |
| dc.contributor.editor | Gabriel Winter | |
| dc.date.accessioned | 2024-04-15T09:57:43Z | |
| dc.date.available | 2024-04-15T09:57:43Z | |
| dc.date.issued | 2014-11-15 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/198939 | |
| dc.description.abstractEn | This work illustrates a practical and efficient method for performing multi-objective optimization using high-order statistics. It is based on a Polynomial Chaos framework, and evolutionary algorithms. In particular, the interest of considering high-order statistics for reducing the number of uncertainties is studied. The feasibility of the proposed method is proved on a Computational Fluid-Dynamics (CFD) real-case application. | |
| dc.language.iso | en | |
| dc.publisher | Springer International Publishing | |
| dc.source.title | Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences | |
| dc.subject.en | High-order statistics | |
| dc.subject.en | Dimension reduction | |
| dc.subject.en | Genetic algorithms | |
| dc.subject.en | Robust optimization | |
| dc.title.en | Multi-objective Design Optimization Using High-Order Statistics for CFD Applications | |
| dc.type | Chapitre d'ouvrage | |
| dc.identifier.doi | 10.1007/978-3-319-11541-2_7 | |
| dc.subject.hal | Physique [physics]/Physique [physics]/Dynamique des Fluides [physics.flu-dyn] | |
| bordeaux.page | 111-126 | |
| bordeaux.volume | 36 | |
| bordeaux.hal.laboratories | Laboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800 | * |
| bordeaux.institution | Université de Bordeaux | |
| bordeaux.institution | Bordeaux INP | |
| bordeaux.institution | CNRS | |
| bordeaux.title.proceeding | Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences | |
| hal.identifier | hal-01091941 | |
| hal.version | 1 | |
| hal.popular | non | |
| hal.audience | Internationale | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-01091941v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=Advances%20in%20Evolutionary%20and%20Deterministic%20Methods%20for%20Design,%20Optimization%20and%20Control%20in%20Engineering%20and%20Sciences&rft.date=2014-11-15&rft.volume=36&rft.spage=111-126&rft.epage=111-126&rft.au=CONGEDO,%20Pietro%20Marco&GERACI,%20Gianluca&ABGRALL,%20R%C3%A9mi&IACCARINO,%20Gianluca&rft.genre=unknown |
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