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Efficient optimization procedure in non-linear fluid-structure interaction problem: Application to mainsail trimming in upwind conditions

Article dans une revue avec comité de lecture
Auteur
SACHER, Matthieu
ccHAUVILLE, Frederic
13094 Institut de Recherche de l'Ecole Navale [IRENAV]
DUVIGNEAU, Régis
412820 Analysis and Control of Unsteady Models for Engineering Sciences [ACUMES]
LE MAÎTRE, Olivier
247329 Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur [LIMSI]
AUBIN, Nicolas
DURAND, Mathieu
233702 K-Epsilon

URI
http://hdl.handle.net/10985/15076
DOI
10.1016/j.jfluidstructs.2016.12.006
Date
2017
Journal
Journal of Fluids and Structures

Résumé

This paper investigates the use of Gaussian processes to solve sail trimming optimization problems. The Gaussian process, used to model the dependence of the performance with the trimming parameters, is constructed from a limited number of performance estimations at carefully selected trimming points, potentially enabling the optimization of complex sail systems with multiple trimming parameters. The proposed approach is tested on a two-parameter trimming for a scaled IMOCA mainsail in upwind sailing conditions. We focus on the robustness of the proposed approach and study especially the sensitivity of the results to noise and model error in the point estimations of the performance. In particular, we contrast the optimization performed on a real physical model set in a wind tunnel with a fully non-linear numerical fluidstructure interaction model of the same experiments. For this problem with a limited number of trimming parameters, the numerical optimization was affordable and found to require a comparable amount of performance estimation as for the experimental case. The results reveal a satisfactory agreement for the numerical and experimental optimal trimming parameters, considering the inherent sources of errors and uncertainties in both numerical and experimental approaches. Sensitivity analyses have been eventually performed in the numerical optimization problem to determine the dominant source of uncertainties and characterize the robustness of the optima.

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  • Institut de Recherche de l’École navale (IRENAV)

Documents liés

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  • Experimental and numerical trimming optimizations for a mainsail in upwind conditions 
    Communication avec acte
    SACHER, Matthieu; ccHAUVILLE, Frederic; DUVIGNEAU, Régis; LE MAITRE, Olivier; AUBIN, Nicolas; DURAND, Mathieu (2016)
    This paper investigates the use of meta-models for optimizing sails trimming. A Gaussian process is used to robustly approximate the dependence of the performance with the trimming parameters to be optimized. The Gaussian ...
  • A classification approach to efficient global optimization in presence of non-computable domains 
    Article dans une revue avec comité de lecture
    SACHER, Matthieu; DUVIGNEAU, Régis; LE MAÎTRE, Olivier; DURAND, Mathieu; BERRINI, Elisa; ccHAUVILLE, Frederic; ccASTOLFI, Jacques Andre (Springer Verlag (Germany), 2018)
    Gaussian-Process based optimization methods have become very popular in recent years for the global optimization of complex systems with high computational costs. These methods rely on the sequential construction of a ...
  • Flexible hydrofoil optimization for the 35th America's cup with constrained ego method 
    Communication avec acte
    SACHER, Matthieu; DURAND, Mathieu; BERRINI, Elisa; ccHAUVILLE, Frederic; DUVIGNEAU, Régis; LE MAITRE, Olivier; ccASTOLFI, Jacques Andre (2017)
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  • Surrogates and Classification approaches for Efficient Global Optimization (EGO) with Inequality Constraints 
    Communication avec acte
    SACHER, Matthieu; DUVIGNEAU, Régis; LE MAITRE, Olivier; DURAND, Mathieu; BERRINI, Elisa; ccHAUVILLE, Frederic; ccASTOLFI, Jacques Andre (2017-05)
    In this work, we compare the use of Gaussian Process (GP) models for the constraints [Schonlau 1997] with a classification approach relying on a Least-Squares Support Vector Machine (LS-SVM) [Suykens and Vandewalle 1999]. ...
  • A Non-Nested Infilling Strategy for Multi-Fidelity based Efficient Global Optimization 
    Article dans une revue avec comité de lecture
    SACHER, Matthieu; LE MAITRE, Olivier; DUVIGNEAU, Régis; ccHAUVILLE, Frederic; DURAND, Mathieu; LOTHODE, Corentin (Begell, 2021)
    Efficient global optimization (EGO) has become a standard approach for the global optimization of complex systems with high computational costs. EGO uses a training set of objective function values computed at selected ...

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