Fiche individuelle
Siyang DENG | ||
Titre | Doctorant | |
Equipe | Outils et Méthodes Numériques | |
Adresse | Ecole Centrale de Lille Cité Scientifique BP 48 - 59651 VILLENEUVE-D'ASCQ | |
Téléphone | +33 (0)3-XX-XX-XX-XX | |
siyang.deng@ec-lille.fr | ||
Publications |
ACLI Revue internationale avec comité de lecture |
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[1] COMPARATIVE STUDY OF METHODS FOR OPTIMIZATION OF ELECTROMAGNETIC DEVICES WITH UNCERTAINTY The International Journal for Computation and Mathematics in Electrical and Electronic Engineering (COMPEL), Vol. 37, N°. 2, pages. 704-717, 04/2018, Abstract DENG Siyang, BRISSET Stéphane, CLENET Stéphane |
This paper compares different probabilistic optimization methods dealing with uncertainties. Reliability-Based Design Optimization is presented as well as various approaches to calculate the probability of failure. They are compared in terms of precision and number of evaluations on mathematical and electromagnetic design problems to highlight the most effective methods. |
[2] Iterative Kriging-based Methods for Expensive Black-Box Models IEEE Transactions on Magnetics, Vol. 54, N°. 3, 03/2018, Abstract DENG Siyang, EL BECHARI Reda, BRISSET Stéphane, CLENET Stéphane |
Reliability-Based Design Optimization (RBDO) in electromagnetic field problems requires the calculation of probability of failure leading to a huge computational cost in the case of expensive models. Three different RBDO approaches using kriging surrogate model are proposed to overcome this difficulty by introducing an approximation of the objective function and constraints. These methods use different infill sampling criteria (ISC) to add samples in the process of optimization or/and in the reliability analysis. Several enrichment criteria and strategies are compared in terms of number of evaluations and accuracy of the solution. |
ACT Conférence internationale avec acte |
[1] Iterative Kriging-based RBDO Methods for Expensive Black-Box Models COMPUMAG 2017, 06/2017, Abstract DENG Siyang, EL BECHARI Reda, BRISSET Stéphane, CLENET Stéphane |
Reliability-Based Design Optimization (RBDO) in electromagnetic field problems requires the calculation of probability of failure leading to huge computational cost in the case of expensive models. Three different types of RBDO approaches using kriging surrogate model are proposed to overcome this difficulty by introducing an approximation of the objective and of the constraints. These methods use different infill searching criteria to add new samples in the process of optimization or/and in the reliability analysis. The enrichment criteria and the best suited enrichment strategies are discussed in this communication. These approaches are compared in terms of number of evaluations and accuracy of the solution. |
[2] COMPARATIVE STUDY OF METHODS FOR OPTIMIZATION OF ELECTROMAGNETIC DEVICES WITH UNCERTAINTY OIPE 2016, 09/2016, Abstract DENG Siyang, BRISSET Stéphane, CLENET Stéphane |
This paper compare different probabilistic optimization methods dealing with uncertainties. Methods of Robust Design Optimization (RDO), Reliability-Based Design Optimization (RBDO) and Reliability-Based Robust Design Optimization (RBRDO) are presented and the approaches to calculate the moments and probability of failure are introduced. Then mathematical and electromagnetic design problems are tested to show the effectiveness of these methods. |
TH Thèse |
[1] Optimisation robuste pour des dispositifs électromagnétiques Thèse, 01/2018, URL, Abstract DENG Siyang |
Méthodes de conception par optimisation robuste et fiable de dispositifs
électrotechniques
Résumé: Cette thèse porte sur les méthodes d'optimisation robuste et fiable. Les
différentes catégories de méthodes d'optimisation stochastique pour traiter les incertitudes
sur les dimensions et les matériaux sont présentées. Ces méthodes visent à trouver une
solution plus robuste et/ou fiable en minimisant la variance de l'objectif et/ou en réduisant la
probabilité de violer les contraintes de faisabilité. Cependant, ces méthodes augmentent le
nombre d'évaluations par rapport à une optimisation déterministe et nécessitent le gradient
qui peut être bruité pour des modèles éléments finis. Ainsi, des stratégies basées sur des
méta-modèles de kriging sont proposées pour approcher des fonctions complexes et donner
des dérivées sans bruit. Des critères d’enrichissement sont utilisés pour affiner la précision
tout en cherchant l’optimum. Différentes stratégies comprenant le choix du critère et le
positionnement de l'enrichissement sont comparées pour mettre en évidence les plus
efficaces. Enfin, les stratégies d’optimisation développées dans cette thèse sont appliquées à
l’optimisation d'un transformateur modélisé par des équations analytiques puis par la
méthode des éléments finis.
Mots-clefs: optimisation, conception, incertitude, robustesse, fiabilité, méta-modèle,
transformateur, modèle d’éléments finis
Methods for Robust and Reliability-based Design Optimization of Electromagnetic Devices
Abstract: This PhD thesis deals with the robust and reliability-based optimization problems
under uncertainty on dimensions and material properties. First, the different categories of
stochastic optimization methods to treat the uncertainty are presented. These methods aim
to find a more robust and/or reliable solution by minimizing the variance of objective and/or
reducing the probability to violate the constraints of feasibility. However, as these methods
increase the number of evaluations compared to deterministic optimization and need the
gradient information that may be noisy when provided by finite element models, they are not
suitable for the time-consuming models. So kriging-based meta-model strategies are
proposed as they can approximate complex functions and give noise-free derivatives. Infill
sampling criteria are used to increase their precision while searching for the optimal solution.
Different strategies including the choice of the criterion and the positioning of sample
enrichment are compared to highlight the most effective ones. Then, the optimization
approaches developed within this research work are applied to the optimization problem of a
transformer modelled with analytic equations and finite element models.
Keywords: design optimization, uncertainty,electromagnetic device, finite element model |
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