Multi-Fidelity Gradient-Based Strategy for Robust Optimization in Computational Fluid Dynamics

Multi-Fidelity Gradient-Based Strategy for Robust Optimization in Computational Fluid Dynamics

Efficient Robust Design Optimization (RDO) strategies coupling a parsimonious uncertainty quantification (UQ) method with a surrogate-based multi-objective genetic algorithm (SMOGA) are investigated for a test problem in computational fluid dynamics (CFD), namely the inverse robust design of an expa...

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Bibliographic Details
Main Authors: Aldo Serafino, Benoit Obert, Paola Cinnella
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Algorithms
Subjects:
robust design optimization
uncertainty quantification
gradient enhanced kriging
method of moments
multi-fidelity surrogate
continuous adjoint
Online Access:https://www.mdpi.com/1999-4893/13/10/248

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https://www.mdpi.com/1999-4893/13/10/248

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